HIVE Lab - User contributions [en]

Volunteership Spring 2027

2026-10-05T13:42:21Z

JewelDias:

== 2027 Spring Volunteer Program Details ==

=== Dates ===
'''Application Deadline'''

December 20th | 12:00 PM ET

'''Volunteer Zoom Kick-Off Meeting'''

Date: TBD

'''Program Dates: January, 2027 – April, 2027''' (13 weeks)

Remote | Hybrid for GW employees and students (Ross Hall 5th floor)

[https://hivelab.biochemistry.gwu.edu/wiki/Volunteership_Fall_2026 Fall 2026 Volunteership] (Closed)

If you are interested, please fill out the [Https://forms.gle/2eXLB5qwofH5dv3m9 Google Form] and submit your resume along with your ranked list of the projects that interest you most. You can also indicate if you would like to focus on specific areas that are of interest to you.

Remote | Hybrid for GW employees and students (Ross Hall 5th floor)
----

=== Volunteer Expectations ===

# Minimum commitment of 10 hours per week. If you want to commit more hours please let us know.
# Progress updates via Slack at least 3 days per week (scrum).
# Volunteers should be responsive to email/slack communications.
# 30-minute Zoom meetings (during regular work hours) once a week or every other week with the assigned project point of contact (POC).
# Volunteers are expected to attend volunteership events such as a symposium.
# Attend some lectures or seminars remotely (max 4-5).
# This volunteership does not allow for vacation time.

'''''Important:''' '''If the scrum is not updated for 2 consecutive working days,''' '''the candidate will be automatically dropped from the program.'''''
----

=== Volunteership Support ===
Each group has dedicated Points of Contact (PoCs) who are your main resource for questions and guidance.

<u>How to Get Help</u>

''Slack Group Channel''

Use your group Slack channel as the primary place to ask questions and share ideas. This is strongly encouraged so everyone can learn together. Direct messages to PoCs are discouraged.

''Office Hours''

PoCs will host group office hours every two weeks once the program begins. These sessions are a space to ask questions, discuss ideas, and collaborate live.

<u>How to get support</u>

- Use the Slack channel as your first point of contact (if you are not yet in the Slack channel, then email your PoC at mazumder_lab@gwu.edu)

- Follow up with your PoCs in the group channel

- Come prepared with questions for office hours

- Participate in discussions and support your peers

Our goal is to create an open, collaborative environment where everyone can learn and contribute.
----

=== Potential Projects ===
We are excited to continue our bioinformatics volunteership program in Summer 2026. This program offers students the opportunity to work on bioinformatics projects supported by agencies such as the NIH, ARPA-H, and FDA. Participants will gain exposure to a variety of activities within a bioinformatics lab, including data analysis, computational biology, and genomics. If you are interested, please email ''mazumder_lab@gwu.edu'' your resume and a ranked list of the projects that interest you most. You can also indicate if you want to focus on specific areas that are of interest to you.

# BiomarkerKB (biomarkerkb.org) project: Biomarker curation project. Involves reading papers and collecting biomarkers.
# GlyGen (glygen.org) project: Review glycomics and glycoproteomics data and curate tissue, disease, and other related information.
# ARGOS (argosdb.org) project: Analyze genomics data using HIVE to identify reference genome assemblies.
# PredictMod (hivelab.biochemistry.gwu.edu/predictmod) project. Curating PMIDs for intervention outcome prediction dataset LLM recommendation training.

''Note: Individuals involved in the above projects with a background in programming and/or machine learning may also undertake additional tasks to support the development of ML models, which can be integrated into PredictMod or used to enhance AI/ML-ready datasets within GlyGen. <u>We are also looking for individuals who have previously worked with us to take on a coordinator role</u>.''
----

==== 1. Glycoscience Resource Discovery and Search Platform ====
POC: Rene Ranzinger

The goal of this project is to develop a production-ready search and discovery platform for glycoscience databases and software tools. The volunteer will enhance an existing prototype that provides a modern, user-friendly alternative to traditional resource catalogs. The platform will enable researchers to efficiently discover relevant databases, software tools, and analytical resources based on their scientific needs.

A major component of the project will be expanding the underlying resource catalog to include not only databases but also software tools and analysis platforms. The volunteer will improve the platform's filtering and search capabilities and investigate how LLMs can be incorporated to support natural language queries

[[:File:GlyGen Volunteership (Fall 2026).pdf|Further information can be found here]]

==== 2. GlyGen AI-Assisted Biocuration Project: Species, Tissue, and Disease Annotation ====
POC: Rene Ranzinger and Urnisha Bhuiyan

The goal of this project is to improve and expand GlyGen's AI-assisted biocuration workflows for metadata normalization and ontology mapping. The volunteer will review the existing species annotation pipeline, evaluate its performance, and refine the species-specific system prompt used by the LLM. Based on lessons learned from species mapping, the project will then extend the methodology to additional biomedical concepts, particularly tissue and disease annotations.

A major focus of the project will be prompt engineering, performance evaluation, and quality assessment. The student will investigate how well the LLM can identify the correct ontology terms when presented with real-world biomedical metadata containing abbreviations, synonyms, misspellings, and incomplete descriptions.

The resulting workflows will support GlyGen's ongoing efforts to harmonize metadata from publications, databases, and legacy resources, ultimately improving data quality and interoperability across the glycoscience ecosystem.

[[:File:GlyGen Volunteership (Fall 2026).pdf|Further information can be found here]]

==== 3. GlyGen Publication Analysis Project ====
POC: Rene Ranzinger and Urnisha Bhuiyan

The goal of this project is to further develop and expand an existing publication analysis and visualization framework that can be used to characterize and understand scientific research communities. Rather than focusing on a single predefined research domain, the analysis framework is designed to support dynamic community discovery through keyword-based literature searches. Publications identified through these searches will then be included in downstream analyses and graphically represented in form of charts, diagrams or graphs.

The resulting analyses will help answer questions such as:

* How large is a particular research community?
* Where are its researchers geographically located?
* Which institutions and investigators are most active?
* Which organizations appear to be central contributors to the field?
* Which research groups overlap with GlyGen's current user and collaborator communities?

* Which potentially important communities or research groups are currently underrepresented in GlyGen outreach efforts?

Ultimately, the analysis may be integrated with GlyGen usage metrics, such as Google Analytics data, to identify regions and research hotspots where glycobiology research is active, but GlyGen adoption appears limited. Such information can help guide future outreach, training, and community engagement activities.

[[:File:GlyGen Volunteership (Fall 2026).pdf|Further information can be found here]]

'''4. Glycoscience Educational Chatbot'''

POC: Sujeet Kulkarni

The goal of this project is to develop a beta version of the Glycoscience Educational Chatbot that can be deployed on a web server and evaluated by a pilot group of users. The student will analyze the strengths and limitations of the current alpha version and implement improvements that enhance usability, reliability, performance, and safety. Particular emphasis will be placed on improving the system&#39;s guardrails to ensure that responses remain focused on educational content, minimize hallucinations, and appropriately handle questions outside the scope of the knowledge base. The completed beta version will support formal user testing by researchers and

educators, providing valuable feedback for future development and broader deployment.

[[:File:GlyGen Volunteership (Fall 2026).pdf|Further information can be found here]]

==== 5. PredictMod Machine Learning (ML) Modeling Project ====
POC: Pat McNeely

Volunteers will conduct ML modeling using publicly-available -omics datasets that were previously identified (see our [[Recommended Publications for Intervention Outcome Prediction Models|Recommended Publications for IOPMs]] page). This volunteership will involve data harmonization, model training, and pipeline documentation.

Tasks associated with this project include:

# Exploring and understanding the data found in relevant PMIDs that can be used to train intervention outcome prediction models.
# Preparing the data for model training and model performance evaluation
# Testing the modeling tutorial, PredictMod platform, and associated project tools
# Documentation of the ML pipeline and testing results

Deliverables for this project include:

# ML-ready datasets & trained model scripts pushed to GitHub
# Pipeline documentation captured in BioCompute Objects (BCOs) and testing reports
# Volunteership documentation (final report, progress updates, symposium presentation)

Interested individuals should reach out to pmcneely@gwu.edu. Please note that this project requires attendance at biweekly meetings and a final presentation of your work.

==== 6. BiomarkerKB Biocuration Project ====
POC: Jeet Vora (primary), Maria Kim, Cyrus Au-Yeung

[https://biomarkerkb.org/about/ BiomarkerKB] is a biomedical knowledgebase project focused on harmonizing and structuring biomarker knowledge from scientific literature and public resources. We are currently recruiting individuals with experience working with LLMs (e.g. Claude, ChatGPT) to support the following tasks:

# '''Validation of existing published biomarkers from scientific literature (JV, MK, CA)'''
#* Review and validate previously reported biomarkers by checking the original literature, confirming evidence support, and standardizing biomarker annotations
#* Assess the evidence strength of biomarkers and identify additional literature to strengthen the support for biomarker claims
# '''Curation of novel biomarkers from scientific literature (MK)'''
#* Curate high-quality biomarkers for a selected disease area, organize the findings into a structured dataset
#* Standardize biomarker representations using controlled vocabularies and ontologies and classify biomarkers by their biomarker types
#* Construct and test-query a disease-specific biomarker knowledge graph (optional)
# '''Electronic Health Records Normal Entity Data Integration (JV)'''
#* Identify relevant EHR data elements (lab tests, diagnoses, procedures)
#* Map entities to standard terminologies (e.g., SNOMED CT, LOINC, ICD codes)
#* Resolve ambiguities and inconsistencies in mapping, clinical terminology
# '''Front-end testing for BiomarkerKB.org (MK, JV)'''
#* Test the BiomarkerKB web interface for functionality and data presentation, and document issues / improvement suggestions for the development team
# '''Benchmarking and LLM-based biomarker extraction (optional*) (CA)'''
#* Construct manually curated biomarker reference sets in the glycobiology domain to support benchmarking of LLM-based knowledge extraction pipelines.
#* Apply an LLM workflow to extract disease-specific biomarkers from literature and comparing model outputs against the manually curated benchmark sets

''Note:'' Participation in the benchmarking and LLM-based biomarker extraction subproject depends on sufficient progress in either task 1 or task 2. Volunteers are expected to first complete either validation of an LLM-extracted glycobiology subset or comprehensive curation of a disease-specific biomarker set before beginning this component. Because this volunteership is structured around a 20-hour-per-week commitment, participation in this part is not guaranteed.

Individuals interested in this opportunity may reach out to Jeet Vora ([mailto:jeetvora@gwu.edu jeetvora@gwu.edu]) for project details.
----

=== Requirements for Completion ===
'''Note:''' The following are mandatory. Failure to complete any will result in an incomplete volunteer record.

==== Documentation ====
All volunteers must maintain adequate documentation of their work, including written protocols and scripts submitted to GitHub.

==== Written Report ====
Submit a 1–2 page summary of your tasks and accomplishments to the Admin during the final week of your program.

==== Presentation & Slide Submission ====
Present your work last week of the 13-week period.

Slides must be submitted to the POCs.
----

=== Completion Certificate ===
A certificate of completion and a letter of recommendation will be provided to all participants who successfully complete the program. Additional recognition will be given to the top three volunteers with exceptional presentations at the end of the program.
----

=== Contact ===
mazumder_lab@gwu.edu.
----'''Volunteers'''

<nowiki>*</nowiki>Returning volunteer.

<sup>†</sup>GW Masters Degree Student

<sup>‡</sup>Not directly involved in the semester curriculum; long-term volunteer.

== Spring 2027 Symposium ==
The Summer symposium will be held virtually. '''Date:''' TBD

'''Time:''' TBD

'''Zoom Link''' - TBA

=== Agenda (All times are in Eastern Standard Time) ===
{| class="wikitable"
!Time
!Project
!Presentation Title
!Presenter(s)
|-
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|}

Volunteership Spring 2027

2026-10-05T13:40:37Z

JewelDias:

== 2027 Spring Volunteer Program Details ==

=== Dates ===
'''Application Deadline'''

December 20th | 12:00 PM ET

'''Volunteer Zoom Kick-Off Meeting'''

Date: TBD

'''Program Dates: January, 2027 – April, 2027''' (13 weeks)

Remote | Hybrid for GW employees and students (Ross Hall 5th floor)

[https://hivelab.biochemistry.gwu.edu/wiki/Volunteership_Fall_2026 Fall 2026 Volunteership] (Closed)

If you are interested, please fill out the [./Https://forms.gle/2eXLB5qwofH5dv3m9 Google Form and] submit your resume along with your ranked list of the projects that interest you most. You can also indicate if you would like to focus on specific areas that are of interest to you.

Remote | Hybrid for GW employees and students (Ross Hall 5th floor)
----

=== Volunteer Expectations ===

# Minimum commitment of 10 hours per week. If you want to commit more hours please let us know.
# Progress updates via Slack at least 3 days per week (scrum).
# Volunteers should be responsive to email/slack communications.
# 30-minute Zoom meetings (during regular work hours) once a week or every other week with the assigned project point of contact (POC).
# Volunteers are expected to attend volunteership events such as a symposium.
# Attend some lectures or seminars remotely (max 4-5).
# This volunteership does not allow for vacation time.

'''''Important:''' '''If the scrum is not updated for 2 consecutive working days,''' '''the candidate will be automatically dropped from the program.'''''
----

=== Volunteership Support ===
Each group has dedicated Points of Contact (PoCs) who are your main resource for questions and guidance.

<u>How to Get Help</u>

''Slack Group Channel''

Use your group Slack channel as the primary place to ask questions and share ideas. This is strongly encouraged so everyone can learn together. Direct messages to PoCs are discouraged.

''Office Hours''

PoCs will host group office hours every two weeks once the program begins. These sessions are a space to ask questions, discuss ideas, and collaborate live.

<u>How to get support</u>

- Use the Slack channel as your first point of contact (if you are not yet in the Slack channel, then email your PoC at mazumder_lab AT gwu.edu)

- Follow up with your PoCs in the group channel

- Come prepared with questions for office hours

- Participate in discussions and support your peers

Our goal is to create an open, collaborative environment where everyone can learn and contribute.
----

=== Potential Projects ===
We are excited to continue our bioinformatics volunteership program in Summer 2026. This program offers students the opportunity to work on bioinformatics projects supported by agencies such as the NIH, ARPA-H, and FDA. Participants will gain exposure to a variety of activities within a bioinformatics lab, including data analysis, computational biology, and genomics. If you are interested, please email ''mazumder_lab@gwu.edu'' your resume and a ranked list of the projects that interest you most. You can also indicate if you want to focus on specific areas that are of interest to you.

# BiomarkerKB (biomarkerkb.org) project: Biomarker curation project. Involves reading papers and collecting biomarkers.
# GlyGen (glygen.org) project: Review glycomics and glycoproteomics data and curate tissue, disease, and other related information.
# ARGOS (argosdb.org) project: Analyze genomics data using HIVE to identify reference genome assemblies.
# PredictMod (hivelab.biochemistry.gwu.edu/predictmod) project. Curating PMIDs for intervention outcome prediction dataset LLM recommendation training.

''Note: Individuals involved in the above projects with a background in programming and/or machine learning may also undertake additional tasks to support the development of ML models, which can be integrated into PredictMod or used to enhance AI/ML-ready datasets within GlyGen. <u>We are also looking for individuals who have previously worked with us to take on a coordinator role</u>.''
----

==== 1. Glycoscience Resource Discovery and Search Platform ====
POC: Rene Ranzinger

The goal of this project is to develop a production-ready search and discovery platform for glycoscience databases and software tools. The volunteer will enhance an existing prototype that provides a modern, user-friendly alternative to traditional resource catalogs. The platform will enable researchers to efficiently discover relevant databases, software tools, and analytical resources based on their scientific needs.

A major component of the project will be expanding the underlying resource catalog to include not only databases but also software tools and analysis platforms. The volunteer will improve the platform's filtering and search capabilities and investigate how LLMs can be incorporated to support natural language queries

[[:File:GlyGen Volunteership (Fall 2026).pdf|Further information can be found here]]

==== 2. GlyGen AI-Assisted Biocuration Project: Species, Tissue, and Disease Annotation ====
POC: Rene Ranzinger and Urnisha Bhuiyan

The goal of this project is to improve and expand GlyGen's AI-assisted biocuration workflows for metadata normalization and ontology mapping. The volunteer will review the existing species annotation pipeline, evaluate its performance, and refine the species-specific system prompt used by the LLM. Based on lessons learned from species mapping, the project will then extend the methodology to additional biomedical concepts, particularly tissue and disease annotations.

A major focus of the project will be prompt engineering, performance evaluation, and quality assessment. The student will investigate how well the LLM can identify the correct ontology terms when presented with real-world biomedical metadata containing abbreviations, synonyms, misspellings, and incomplete descriptions.

The resulting workflows will support GlyGen's ongoing efforts to harmonize metadata from publications, databases, and legacy resources, ultimately improving data quality and interoperability across the glycoscience ecosystem.

[[:File:GlyGen Volunteership (Fall 2026).pdf|Further information can be found here]]

==== 3. GlyGen Publication Analysis Project ====
POC: Rene Ranzinger and Urnisha Bhuiyan

The goal of this project is to further develop and expand an existing publication analysis and visualization framework that can be used to characterize and understand scientific research communities. Rather than focusing on a single predefined research domain, the analysis framework is designed to support dynamic community discovery through keyword-based literature searches. Publications identified through these searches will then be included in downstream analyses and graphically represented in form of charts, diagrams or graphs.

The resulting analyses will help answer questions such as:

* How large is a particular research community?
* Where are its researchers geographically located?
* Which institutions and investigators are most active?
* Which organizations appear to be central contributors to the field?
* Which research groups overlap with GlyGen's current user and collaborator communities?

* Which potentially important communities or research groups are currently underrepresented in GlyGen outreach efforts?

Ultimately, the analysis may be integrated with GlyGen usage metrics, such as Google Analytics data, to identify regions and research hotspots where glycobiology research is active, but GlyGen adoption appears limited. Such information can help guide future outreach, training, and community engagement activities.

[[:File:GlyGen Volunteership (Fall 2026).pdf|Further information can be found here]]

'''4. Glycoscience Educational Chatbot'''

POC: Sujeet Kulkarni

The goal of this project is to develop a beta version of the Glycoscience Educational Chatbot that can be deployed on a web server and evaluated by a pilot group of users. The student will analyze the strengths and limitations of the current alpha version and implement improvements that enhance usability, reliability, performance, and safety. Particular emphasis will be placed on improving the system&#39;s guardrails to ensure that responses remain focused on educational content, minimize hallucinations, and appropriately handle questions outside the scope of the knowledge base. The completed beta version will support formal user testing by researchers and

educators, providing valuable feedback for future development and broader deployment.

[[:File:GlyGen Volunteership (Fall 2026).pdf|Further information can be found here]]

==== 5. PredictMod Machine Learning (ML) Modeling Project ====
POC: Pat McNeely

Volunteers will conduct ML modeling using publicly-available -omics datasets that were previously identified (see our [[Recommended Publications for Intervention Outcome Prediction Models|Recommended Publications for IOPMs]] page). This volunteership will involve data harmonization, model training, and pipeline documentation.

Tasks associated with this project include:

# Exploring and understanding the data found in relevant PMIDs that can be used to train intervention outcome prediction models.
# Preparing the data for model training and model performance evaluation
# Testing the modeling tutorial, PredictMod platform, and associated project tools
# Documentation of the ML pipeline and testing results

Deliverables for this project include:

# ML-ready datasets & trained model scripts pushed to GitHub
# Pipeline documentation captured in BioCompute Objects (BCOs) and testing reports
# Volunteership documentation (final report, progress updates, symposium presentation)

Interested individuals should reach out to pmcneely@gwu.edu. Please note that this project requires attendance at biweekly meetings and a final presentation of your work.

==== 6. BiomarkerKB Biocuration Project ====
POC: Jeet Vora (primary), Maria Kim, Cyrus Au-Yeung

[https://biomarkerkb.org/about/ BiomarkerKB] is a biomedical knowledgebase project focused on harmonizing and structuring biomarker knowledge from scientific literature and public resources. We are currently recruiting individuals with experience working with LLMs (e.g. Claude, ChatGPT) to support the following tasks:

# '''Validation of existing published biomarkers from scientific literature (JV, MK, CA)'''
#* Review and validate previously reported biomarkers by checking the original literature, confirming evidence support, and standardizing biomarker annotations
#* Assess the evidence strength of biomarkers and identify additional literature to strengthen the support for biomarker claims
# '''Curation of novel biomarkers from scientific literature (MK)'''
#* Curate high-quality biomarkers for a selected disease area, organize the findings into a structured dataset
#* Standardize biomarker representations using controlled vocabularies and ontologies and classify biomarkers by their biomarker types
#* Construct and test-query a disease-specific biomarker knowledge graph (optional)
# '''Electronic Health Records Normal Entity Data Integration (JV)'''
#* Identify relevant EHR data elements (lab tests, diagnoses, procedures)
#* Map entities to standard terminologies (e.g., SNOMED CT, LOINC, ICD codes)
#* Resolve ambiguities and inconsistencies in mapping, clinical terminology
# '''Front-end testing for BiomarkerKB.org (MK, JV)'''
#* Test the BiomarkerKB web interface for functionality and data presentation, and document issues / improvement suggestions for the development team
# '''Benchmarking and LLM-based biomarker extraction (optional*) (CA)'''
#* Construct manually curated biomarker reference sets in the glycobiology domain to support benchmarking of LLM-based knowledge extraction pipelines.
#* Apply an LLM workflow to extract disease-specific biomarkers from literature and comparing model outputs against the manually curated benchmark sets

''Note:'' Participation in the benchmarking and LLM-based biomarker extraction subproject depends on sufficient progress in either task 1 or task 2. Volunteers are expected to first complete either validation of an LLM-extracted glycobiology subset or comprehensive curation of a disease-specific biomarker set before beginning this component. Because this volunteership is structured around a 20-hour-per-week commitment, participation in this part is not guaranteed.

Individuals interested in this opportunity may reach out to Jeet Vora ([mailto:jeetvora@gwu.edu jeetvora@gwu.edu]) for project details.
----

=== Requirements for Completion ===
'''Note:''' The following are mandatory. Failure to complete any will result in an incomplete volunteer record.

==== Documentation ====
All volunteers must maintain adequate documentation of their work, including written protocols and scripts submitted to GitHub.

==== Written Report ====
Submit a 1–2 page summary of your tasks and accomplishments to the Admin during the final week of your program.

==== Presentation & Slide Submission ====
Present your work last week of the 9-week period.

Slides must be submitted to the POCs.
----

=== Completion Certificate ===
A certificate of completion and a letter of recommendation will be provided to all participants who successfully complete the program. Additional recognition will be given to the top three volunteers with exceptional presentations at the end of the program.
----

=== Contact ===
mazumder_lab@gwu.edu.
----'''Volunteers'''

<nowiki>*</nowiki>Returning volunteer.

<sup>†</sup>GW Masters Degree Student

<sup>‡</sup>Not directly involved in the semester curriculum; long-term volunteer.

== Spring 2027 Symposium ==
The Summer symposium will be held virtually. '''Date:''' TBD

'''Time:''' TBD

'''Zoom Link''' - TBA

=== Agenda (All times are in Eastern Standard Time) ===
{| class="wikitable"
!Time
!Project
!Presentation Title
!Presenter(s)
|-
|
|
|
|
|-
|
|
|
|
|-
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|
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|-
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| colspan="2" |
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|}

Projects

2026-10-02T22:19:08Z

JewelDias: /./

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<div style="margin:0.4em; text-align:center;">
<div style="font-size:160%; padding:.1em;">Current Projects</div>
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<h3>[https://hive.biochemistry.gwu.edu/dna.cgi?cmd=main The High-performance Integrated Virtual Environment (HIVE) platform]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
HIVE is a cloud-based environment optimized for the storage and analysis of extra-large data, such as biomedical data, clinical data, next-generation sequencing (NGS) data, mass spectrometry files, confocal microscopy images, post-market surveillance data, medical recall data, and many others. HIVE provides secure web access for authorized users to deposit, retrieve, annotate and compute on Big Data, and analyze the outcomes using web user interfaces. [https://docs.google.com/document/d/1F5iq00uKkJfdSsbwanvKOy-nPnwijH56mwbwa_HhzfY/edit?tab=t.0#heading=h.7dlfmngwfzih More here].

The HIVE platform and associated algorithms such as CensuScope and HIVE-Hexagon is used to support Metgenomics analysis infrastructure.<br><br>
[[GW-HIVE WIKI]]

[[METAGENOMICS WIKI]]

</div>
</div>
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<h3>[https://data.argosdb.org/ FDA-ARGOS Project (Food and Drug Administration-dAtabase for Regulatory-Grade micrObial Sequences)]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
The FDA-ARGOS Project (Food and Drug Administration-dAtabase for Regulatory-Grade micrObial Sequences) is a collaborative effort to create a high-quality genomic database for identifying and characterizing microbial pathogens. Developed in partnership with the FDA, University of Maryland, and NCBI, the project provides regulatory-grade genomic data, crucial for public health and diagnostic use. Expanded in 2021 with support from GWU, Temple University, and Embleema, FDA-ARGOS aims to enhance infectious disease research through rigorous quality control protocols. The ArgosDB hosts this data, offering downloadable sequences and reproducible workflows for research and regulatory applications.[https://www.fda.gov/medical-devices/science-and-research-medical-devices/database-reference-grade-microbial-sequences-fda-argos More here].<br><br>
[[FDA-ARGOS WIKI]]
</div>
</div>

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<h3>[https://www.biocomputeobject.org/ BioCompute Objects (BCO)]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
The BioCompute is FDA funded project to establish a framework for community-based development of standards for harmonization of High-throughput Sequencing (HTS), standardization of data formats, promotion of interoperability, and bioinformatics verification protocols. The BioCompute Object (BCO) was developed in the High-throughput Sequencing Computational Standards for Regulatory Sciences (HTS-CSRS) initiative in the BioCompute Objects Portal (BOP), a web portal to serve as a collaborative ground to encourage a dialogue to facilitate interoperability between different bioinformatic pipelines, industries, and developers. HIVE capabilities have been leveraged to support the development of the BCO. The BCO is versatile and adaptable to other common HTS analysis platforms. [https://docs.google.com/document/d/1WQFZm_PFiQXob4NyOKq6y-2ywnbmNoFHSS27fYf3l4Y/edit?tab=t.0#heading=h.bs8eki17tykx More here].<br><br>
[https://wiki.biocomputeobject.org/Main_Page BIOCOMPUTE OBJECTS WIKI]
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<h3>[https://www.glygen.org/ GlyGen]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
GlyGen (gly-glycobiology; gen-information), [https://www.glygen.org/<nowiki>] is an advanced glycoinformatics resource developed to facilitate discovery in basic and translational glycobiology research along with enhancing the integration of multidisciplinary information from diverse resources. GlyGen includes knowledge about molecular, biophysical and functional properties of glycans, genes, and proteins organized in pathways and ontologies, plus a rapidly growing body of biological big data related to cancer mutation and expression. GlyGen adopts an innovative user-driven approach for implementing, prioritizing and knowledge disseminating tools to address the questions and needs of glycobiology community. GlyGen is funded by the National Institute of General Medical Sciences under the grant # 1R24GM146616 - 01 and the National Institutes of Health Office of Strategic Coordination - The Common Fund under the grant # 1OT2OD032092. More information about GlyGen - </nowiki>https://www.glygen.org/about/ <br><br>
[https://wiki.glygen.org/Main_Page GlyGen WIKI]
</div>
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<h3>[https://hivelab.biochemistry.gwu.edu/predictmod PredictMod]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
PredictMod is an application designed to predict the outcome of an intervention prior to a patient initiating treatment. Our goal is to provide clinicians with a powerful decision making tool that enhances clinical understanding of patient-level data. The PredictMod platform utilizes machine learning tools and complex datasets based on electronic health records, gut microbiome, and -omics data to forecast patient outcomes, often in response to treatment for a particular condition. While our primary condition of interest is Prediabetes, the tool is designed to be used for a variety of conditions, interventions, and data types. <br> <br>
[https://hivelab.biochemistry.gwu.edu/wiki/PredictMod PredictMod WIKI]
</div>
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<h3>[[GW-FEAST]]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
The GW Federated Ecosystems for Analytics and Standardized Technologies (GW-FEAST) project is part of the ARPA-H FEAST performer team initiative that includes academic and industry partners. The goal of the ARPA-H performer teams is “to create bridges across data silos to make health data more accessible and usable”. <br><br>
[https://hivelab.biochemistry.gwu.edu/wiki/GW-FEAST GW-FEAST WIKI]
</div>
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<h3>[https://biomarkerkb.org/ Biomarker Knowledgebase]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
The Biomarker Partnership is a CFDE sponsored project to develop a knowledgebase that will organize and integrate biomarker data from different public sources. The data will be connected to contextual information to show a novel systems-level view of biomarkers. The motivation for this project is to improve the harmonization and organization of biomarker data. This will be done by mapping biomarkers from public sources to, and across, CF data elements. This mapping will bridge knowledge across multiple DCCs and biomedical disciplines.<br><br>
[https://wiki.biomarkerkb.org/Main_Page BioMarkerKB WIKI]
</div>
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<div style="margin:0.4em; text-align:center;">
<div style="font-size:160%; padding:.1em;">Volunteership Semesters</div>[[Volunteership Spring 2027]]
[[Volunteership Fall 2026]]

[[Volunteership Summer 2026]]

[[Volunteership Spring 2026]]

[[Volunteership Fall 2025]]

[[Volunteership 2025|Volunteership Summer 2025]]
</div>
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<div style="margin:0.4em; text-align:center;">
<div style="font-size:160%; padding:.1em;">Past Projects</div>
</div>
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<h3>[https://hivelab.tst.biochemistry.gwu.edu/gfkb Gut Microbiome Analytic System (Microbiome)]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
The HIVE team received NSF funding to develop a Gut Microbiome Monitoring System (GutFeeling) as a tool which when used over time will allow users to rectify their dietary (such as consumption of probiotics and prebiotics) and other lifestyle habits and to help restore their normal microbiome. Rapid analysis of the large amount of metagenomic data, a major bottleneck, has been resolved by our group through the development of a novel algorithm and accompanying software called CensuScope. Through analysis of healthy gut microbiome data, we are actively developing a Knowledge Base (GutFeelingKB) to provide a clearer picture of not only an ideal personalized microbiome but also establish baseline characteristics for each customer. The Mazumder Lab is collaborating with the Milken School of Public Health and Kamtek Sequencing Facility to investigate the relationship between bacterial species commonly present in the digestive tract, diet, physical activity, lifestyle habits, and metabolic risk factors. [https://docs.google.com/document/d/18WyVTJrrf-FR0sHt634vO8Lwel-4OQxP9sNar7gYYro/edit?tab=t.0#heading=h.7qbm3f7lky31 More here].
</div>
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<h3>HIVE-EQAPOL Project on HIVE NGS Data Processing and Analysis</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
For this project, our group works closely with the External Quality Assurance Program Oversight Laboratory (EQAPOL) team to conduct HIV NGS data analysis and collaborate in terms of analyzing, storing, and tracking HIV NGS Data. Reliable identification of strains is critical for developing new assays, validating assay platforms, assisting regulators to evaluate test kits, monitoring HIV drug resistance, and informing vaccine development. The HIVE tools and platform are used for virus identification, recombination analysis, and clone discovery.
</div>
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<h3>[https://www.oncomx.org/ OncoMX]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
The OncoMX mission is to create an integrated cancer mutation and expression resource for exploring cancer biomarkers. OncoMX is a collaboration between the George Washington University (GW), NASA's Jet Propulsion Laboratory (JPL), the Swiss Institute of Bioinformatics (SIB), and the University of Delaware (UD). The core knowledgebase of OncoMX is derived from BioMuta and BioXpress integrated cancer mutation and expression databases which are actively maintained. Normal expression data from Bgee and custom text mining software augment the cancer data to improve functional interpretation of the reported variants and expression profiles. All data are wrapped into the OncoMX database and web portal, mapped to additional functional information from NCI Early Detection Research Network (EDRN) and Reactome. It is expected that the large-scale integration of cancer data and supporting information, provided by OncoMX with direct community feedback, will benefit cancer research by improving synthesis of information and may make earlier detection a reality.
</div>
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<h3>[https://hive.biochemistry.gwu.edu/dna.cgi?cmd=main Glycoproteomics Characterization Workflow and Data-Analysis Pipeline for Vaccines and Biosimilars]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
In this FDA funded project we are extending High-performance Integrated Virtual Environment (HIVE) capabilities through the development and integration of software tools and datasets for comparative analysis of glycoproteins. Glycomic analysis has many angles and has been extensively reviewed in recent literature. We propose to rely on the independent development of the glycomics field and incorporate these approaches in the HIVE pipeline as they mature while we develop a standardized glycoinformatics pipeline that will benefit investigators and regulators at the FDA.
</div>
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<div style="font-size:160%; padding:.1em;">RESOURCES</div>
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<h3>[[Tool Resources]]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
    '''''Main article:''' [[Tool Resources]]''<br>There are a variety of bioinformatic tool resources developed by our team.
<br />
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<h3>[[Dataset Resources]]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
    '''''Main article:''' [[Dataset Resources]]''<br>There are a variety of bioinformatic dataset resources integrated by our team.
</div>
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Volunteership Spring 2027

2026-10-02T22:18:25Z

JewelDias: /* Dates */

== 2027 Spring Volunteer Program Details ==

=== Dates ===
'''Application Deadline'''

January 2nd | 12:00 PM ET

'''Volunteer Zoom Kick-Off Meeting'''

Date: TBD

'''Volunteer Zoom Kick-Off Meeting'''

TBD

'''Program Dates: January, 2027 – April, 2027''' (13 weeks)

Remote | Hybrid for GW employees and students (Ross Hall 5th floor)

[[Volunteership Fall 2025|Fall 2026 Volunteership]] (Closed)

If you are interested, please email mazumder_lab@gwu.edu your resume and a ranked list of the [[Volunteership Fall 2026#Potential Projects|projects]] that interest you most. You can also indicate if you want to focus on specific areas that are of interest to you.

Remote | Hybrid for GW employees and students (Ross Hall 5th floor)
----

=== Volunteer Expectations ===

# Minimum commitment of 10 hours per week. If you want to commit more hours please let us know.
# Progress updates via Slack at least 3 days per week (scrum).
# Volunteers should be responsive to email/slack communications.
# 30-minute Zoom meetings (during regular work hours) once a week or every other week with the assigned project point of contact (POC).
# Volunteers are expected to attend volunteership events such as a symposium.
# Attend some lectures or seminars remotely (max 4-5).
# This volunteership does not allow for vacation time.

'''''Important:''' '''If the scrum is not updated for 2 consecutive working days,''' '''the candidate will be automatically dropped from the program.'''''
----

=== Volunteership Support ===
Each group has dedicated Points of Contact (PoCs) who are your main resource for questions and guidance.

<u>How to Get Help</u>

''Slack Group Channel''

Use your group Slack channel as the primary place to ask questions and share ideas. This is strongly encouraged so everyone can learn together. Direct messages to PoCs are discouraged.

''Office Hours''

PoCs will host group office hours every two weeks once the program begins. These sessions are a space to ask questions, discuss ideas, and collaborate live.

<u>How to get support</u>

- Use the Slack channel as your first point of contact (if you are not yet in the Slack channel, then email your PoC at mazumder_lab AT gwu.edu)

- Follow up with your PoCs in the group channel

- Come prepared with questions for office hours

- Participate in discussions and support your peers

Our goal is to create an open, collaborative environment where everyone can learn and contribute.
----

=== Potential Projects ===
We are excited to continue our bioinformatics volunteership program in Summer 2026. This program offers students the opportunity to work on bioinformatics projects supported by agencies such as the NIH, ARPA-H, and FDA. Participants will gain exposure to a variety of activities within a bioinformatics lab, including data analysis, computational biology, and genomics. If you are interested, please email ''mazumder_lab@gwu.edu'' your resume and a ranked list of the projects that interest you most. You can also indicate if you want to focus on specific areas that are of interest to you.

# BiomarkerKB (biomarkerkb.org) project: Biomarker curation project. Involves reading papers and collecting biomarkers.
# GlyGen (glygen.org) project: Review glycomics and glycoproteomics data and curate tissue, disease, and other related information.
# ARGOS (argosdb.org) project: Analyze genomics data using HIVE to identify reference genome assemblies.
# PredictMod (hivelab.biochemistry.gwu.edu/predictmod) project. Curating PMIDs for intervention outcome prediction dataset LLM recommendation training.

''Note: Individuals involved in the above projects with a background in programming and/or machine learning may also undertake additional tasks to support the development of ML models, which can be integrated into PredictMod or used to enhance AI/ML-ready datasets within GlyGen. <u>We are also looking for individuals who have previously worked with us to take on a coordinator role</u>.''
----

==== 1. Glycoscience Resource Discovery and Search Platform ====
POC: Rene Ranzinger

The goal of this project is to develop a production-ready search and discovery platform for glycoscience databases and software tools. The volunteer will enhance an existing prototype that provides a modern, user-friendly alternative to traditional resource catalogs. The platform will enable researchers to efficiently discover relevant databases, software tools, and analytical resources based on their scientific needs.

A major component of the project will be expanding the underlying resource catalog to include not only databases but also software tools and analysis platforms. The volunteer will improve the platform's filtering and search capabilities and investigate how LLMs can be incorporated to support natural language queries

[[:File:GlyGen Volunteership (Fall 2026).pdf|Further information can be found here]]

==== 2. GlyGen AI-Assisted Biocuration Project: Species, Tissue, and Disease Annotation ====
POC: Rene Ranzinger and Urnisha Bhuiyan

The goal of this project is to improve and expand GlyGen's AI-assisted biocuration workflows for metadata normalization and ontology mapping. The volunteer will review the existing species annotation pipeline, evaluate its performance, and refine the species-specific system prompt used by the LLM. Based on lessons learned from species mapping, the project will then extend the methodology to additional biomedical concepts, particularly tissue and disease annotations.

A major focus of the project will be prompt engineering, performance evaluation, and quality assessment. The student will investigate how well the LLM can identify the correct ontology terms when presented with real-world biomedical metadata containing abbreviations, synonyms, misspellings, and incomplete descriptions.

The resulting workflows will support GlyGen's ongoing efforts to harmonize metadata from publications, databases, and legacy resources, ultimately improving data quality and interoperability across the glycoscience ecosystem.

[[:File:GlyGen Volunteership (Fall 2026).pdf|Further information can be found here]]

==== 3. GlyGen Publication Analysis Project ====
POC: Rene Ranzinger and Urnisha Bhuiyan

The goal of this project is to further develop and expand an existing publication analysis and visualization framework that can be used to characterize and understand scientific research communities. Rather than focusing on a single predefined research domain, the analysis framework is designed to support dynamic community discovery through keyword-based literature searches. Publications identified through these searches will then be included in downstream analyses and graphically represented in form of charts, diagrams or graphs.

The resulting analyses will help answer questions such as:

* How large is a particular research community?
* Where are its researchers geographically located?
* Which institutions and investigators are most active?
* Which organizations appear to be central contributors to the field?
* Which research groups overlap with GlyGen's current user and collaborator communities?

* Which potentially important communities or research groups are currently underrepresented in GlyGen outreach efforts?

Ultimately, the analysis may be integrated with GlyGen usage metrics, such as Google Analytics data, to identify regions and research hotspots where glycobiology research is active, but GlyGen adoption appears limited. Such information can help guide future outreach, training, and community engagement activities.

[[:File:GlyGen Volunteership (Fall 2026).pdf|Further information can be found here]]

'''4. Glycoscience Educational Chatbot'''

POC: Sujeet Kulkarni

The goal of this project is to develop a beta version of the Glycoscience Educational Chatbot that can be deployed on a web server and evaluated by a pilot group of users. The student will analyze the strengths and limitations of the current alpha version and implement improvements that enhance usability, reliability, performance, and safety. Particular emphasis will be placed on improving the system&#39;s guardrails to ensure that responses remain focused on educational content, minimize hallucinations, and appropriately handle questions outside the scope of the knowledge base. The completed beta version will support formal user testing by researchers and

educators, providing valuable feedback for future development and broader deployment.

[[:File:GlyGen Volunteership (Fall 2026).pdf|Further information can be found here]]

==== 5. PredictMod Machine Learning (ML) Modeling Project ====
POC: Pat McNeely

Volunteers will conduct ML modeling using publicly-available -omics datasets that were previously identified (see our [[Recommended Publications for Intervention Outcome Prediction Models|Recommended Publications for IOPMs]] page). This volunteership will involve data harmonization, model training, and pipeline documentation.

Tasks associated with this project include:

# Exploring and understanding the data found in relevant PMIDs that can be used to train intervention outcome prediction models.
# Preparing the data for model training and model performance evaluation
# Testing the modeling tutorial, PredictMod platform, and associated project tools
# Documentation of the ML pipeline and testing results

Deliverables for this project include:

# ML-ready datasets & trained model scripts pushed to GitHub
# Pipeline documentation captured in BioCompute Objects (BCOs) and testing reports
# Volunteership documentation (final report, progress updates, symposium presentation)

Interested individuals should reach out to pmcneely@gwu.edu. Please note that this project requires attendance at biweekly meetings and a final presentation of your work.

==== 6. BiomarkerKB Biocuration Project ====
POC: Jeet Vora (primary), Maria Kim, Cyrus Au-Yeung

[https://biomarkerkb.org/about/ BiomarkerKB] is a biomedical knowledgebase project focused on harmonizing and structuring biomarker knowledge from scientific literature and public resources. We are currently recruiting individuals with experience working with LLMs (e.g. Claude, ChatGPT) to support the following tasks:

# '''Validation of existing published biomarkers from scientific literature (JV, MK, CA)'''
#* Review and validate previously reported biomarkers by checking the original literature, confirming evidence support, and standardizing biomarker annotations
#* Assess the evidence strength of biomarkers and identify additional literature to strengthen the support for biomarker claims
# '''Curation of novel biomarkers from scientific literature (MK)'''
#* Curate high-quality biomarkers for a selected disease area, organize the findings into a structured dataset
#* Standardize biomarker representations using controlled vocabularies and ontologies and classify biomarkers by their biomarker types
#* Construct and test-query a disease-specific biomarker knowledge graph (optional)
# '''Electronic Health Records Normal Entity Data Integration (JV)'''
#* Identify relevant EHR data elements (lab tests, diagnoses, procedures)
#* Map entities to standard terminologies (e.g., SNOMED CT, LOINC, ICD codes)
#* Resolve ambiguities and inconsistencies in mapping, clinical terminology
# '''Front-end testing for BiomarkerKB.org (MK, JV)'''
#* Test the BiomarkerKB web interface for functionality and data presentation, and document issues / improvement suggestions for the development team
# '''Benchmarking and LLM-based biomarker extraction (optional*) (CA)'''
#* Construct manually curated biomarker reference sets in the glycobiology domain to support benchmarking of LLM-based knowledge extraction pipelines.
#* Apply an LLM workflow to extract disease-specific biomarkers from literature and comparing model outputs against the manually curated benchmark sets

''Note:'' Participation in the benchmarking and LLM-based biomarker extraction subproject depends on sufficient progress in either task 1 or task 2. Volunteers are expected to first complete either validation of an LLM-extracted glycobiology subset or comprehensive curation of a disease-specific biomarker set before beginning this component. Because this volunteership is structured around a 20-hour-per-week commitment, participation in this part is not guaranteed.

Individuals interested in this opportunity may reach out to Jeet Vora ([mailto:jeetvora@gwu.edu jeetvora@gwu.edu]) for project details.
----

=== Requirements for Completion ===
'''Note:''' The following are mandatory. Failure to complete any will result in an incomplete volunteer record.

==== Documentation ====
All volunteers must maintain adequate documentation of their work, including written protocols and scripts submitted to GitHub.

==== Written Report ====
Submit a 1–2 page summary of your tasks and accomplishments to the Admin during the final week of your program.

==== Presentation & Slide Submission ====
Present your work last week of the 9-week period.

Slides must be submitted to the POCs.
----

=== Completion Certificate ===
A certificate of completion and a letter of recommendation will be provided to all participants who successfully complete the program. Additional recognition will be given to the top three volunteers with exceptional presentations at the end of the program.
----

=== Contact ===
mazumder_lab@gwu.edu.
----'''Volunteers'''

<nowiki>*</nowiki>Returning volunteer.

<sup>†</sup>GW Masters Degree Student

<sup>‡</sup>Not directly involved in the semester curriculum; long-term volunteer.

== Spring 2027 Symposium ==
The Summer symposium will be held virtually. '''Date:''' TBD

'''Time:''' TBD

'''Zoom Link''' - TBA

=== Agenda (All times are in Eastern Standard Time) ===
{| class="wikitable"
!Time
!Project
!Presentation Title
!Presenter(s)
|-
|
|
|
|
|-
|
|
|
|
|-
|
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|-
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|-
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|-
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| colspan="2" |
|
|}

Volunteership Spring 2027

2026-10-02T22:15:29Z

JewelDias: Volunteership Spring 2027

== 2027 Spring Volunteer Program Details ==

=== Dates ===
'''Application Deadline'''

January 2nd | 12:00 PM ET

'''Volunteer Zoom Kick-Off Meeting'''

Date: TBD

'''Program Dates:'''

If you are interested, please email mazumder_lab@gwu.edu your resume and a ranked list of the [[Volunteership Fall 2026#Potential Projects|projects]] that interest you most. You can also indicate if you want to focus on specific areas that are of interest to you.

Remote | Hybrid for GW employees and students (Ross Hall 5th floor)

[[Volunteership Spring 2026|Spring 2026 Volunteership]]

Presentation slides from the Spring 2026 volunteership symposium are publicly available on Zenodo to highlight student research contributions from the program.
----

=== Volunteer Expectations ===

# Minimum commitment of 10 hours per week. If you want to commit more hours please let us know.
# Progress updates via Slack at least 3 days per week (scrum).
# Volunteers should be responsive to email/slack communications.
# 30-minute Zoom meetings (during regular work hours) once a week or every other week with the assigned project point of contact (POC).
# Volunteers are expected to attend volunteership events such as a symposium.
# Attend some lectures or seminars remotely (max 4-5).
# This volunteership does not allow for vacation time.

'''''Important:''' '''If the scrum is not updated for 2 consecutive working days,''' '''the candidate will be automatically dropped from the program.'''''
----

=== Volunteership Support ===
Each group has dedicated Points of Contact (PoCs) who are your main resource for questions and guidance.

<u>How to Get Help</u>

''Slack Group Channel''

Use your group Slack channel as the primary place to ask questions and share ideas. This is strongly encouraged so everyone can learn together. Direct messages to PoCs are discouraged.

''Office Hours''

PoCs will host group office hours every two weeks once the program begins. These sessions are a space to ask questions, discuss ideas, and collaborate live.

<u>How to get support</u>

- Use the Slack channel as your first point of contact (if you are not yet in the Slack channel, then email your PoC at mazumder_lab AT gwu.edu)

- Follow up with your PoCs in the group channel

- Come prepared with questions for office hours

- Participate in discussions and support your peers

Our goal is to create an open, collaborative environment where everyone can learn and contribute.
----

=== Potential Projects ===
We are excited to continue our bioinformatics volunteership program in Summer 2026. This program offers students the opportunity to work on bioinformatics projects supported by agencies such as the NIH, ARPA-H, and FDA. Participants will gain exposure to a variety of activities within a bioinformatics lab, including data analysis, computational biology, and genomics. If you are interested, please email ''mazumder_lab@gwu.edu'' your resume and a ranked list of the projects that interest you most. You can also indicate if you want to focus on specific areas that are of interest to you.

# BiomarkerKB (biomarkerkb.org) project: Biomarker curation project. Involves reading papers and collecting biomarkers.
# GlyGen (glygen.org) project: Review glycomics and glycoproteomics data and curate tissue, disease, and other related information.
# ARGOS (argosdb.org) project: Analyze genomics data using HIVE to identify reference genome assemblies.
# PredictMod (hivelab.biochemistry.gwu.edu/predictmod) project. Curating PMIDs for intervention outcome prediction dataset LLM recommendation training.

''Note: Individuals involved in the above projects with a background in programming and/or machine learning may also undertake additional tasks to support the development of ML models, which can be integrated into PredictMod or used to enhance AI/ML-ready datasets within GlyGen. <u>We are also looking for individuals who have previously worked with us to take on a coordinator role</u>.''
----

==== 1. Glycoscience Resource Discovery and Search Platform ====
POC: Rene Ranzinger

The goal of this project is to develop a production-ready search and discovery platform for glycoscience databases and software tools. The volunteer will enhance an existing prototype that provides a modern, user-friendly alternative to traditional resource catalogs. The platform will enable researchers to efficiently discover relevant databases, software tools, and analytical resources based on their scientific needs.

A major component of the project will be expanding the underlying resource catalog to include not only databases but also software tools and analysis platforms. The volunteer will improve the platform's filtering and search capabilities and investigate how LLMs can be incorporated to support natural language queries

[[:File:GlyGen Volunteership (Fall 2026).pdf|Further information can be found here]]

==== 2. GlyGen AI-Assisted Biocuration Project: Species, Tissue, and Disease Annotation ====
POC: Rene Ranzinger and Urnisha Bhuiyan

The goal of this project is to improve and expand GlyGen's AI-assisted biocuration workflows for metadata normalization and ontology mapping. The volunteer will review the existing species annotation pipeline, evaluate its performance, and refine the species-specific system prompt used by the LLM. Based on lessons learned from species mapping, the project will then extend the methodology to additional biomedical concepts, particularly tissue and disease annotations.

A major focus of the project will be prompt engineering, performance evaluation, and quality assessment. The student will investigate how well the LLM can identify the correct ontology terms when presented with real-world biomedical metadata containing abbreviations, synonyms, misspellings, and incomplete descriptions.

The resulting workflows will support GlyGen's ongoing efforts to harmonize metadata from publications, databases, and legacy resources, ultimately improving data quality and interoperability across the glycoscience ecosystem.

[[:File:GlyGen Volunteership (Fall 2026).pdf|Further information can be found here]]

==== 3. GlyGen Publication Analysis Project ====
POC: Rene Ranzinger and Urnisha Bhuiyan

The goal of this project is to further develop and expand an existing publication analysis and visualization framework that can be used to characterize and understand scientific research communities. Rather than focusing on a single predefined research domain, the analysis framework is designed to support dynamic community discovery through keyword-based literature searches. Publications identified through these searches will then be included in downstream analyses and graphically represented in form of charts, diagrams or graphs.

The resulting analyses will help answer questions such as:

* How large is a particular research community?
* Where are its researchers geographically located?
* Which institutions and investigators are most active?
* Which organizations appear to be central contributors to the field?
* Which research groups overlap with GlyGen's current user and collaborator communities?

* Which potentially important communities or research groups are currently underrepresented in GlyGen outreach efforts?

Ultimately, the analysis may be integrated with GlyGen usage metrics, such as Google Analytics data, to identify regions and research hotspots where glycobiology research is active, but GlyGen adoption appears limited. Such information can help guide future outreach, training, and community engagement activities.

[[:File:GlyGen Volunteership (Fall 2026).pdf|Further information can be found here]]

'''4. Glycoscience Educational Chatbot'''

POC: Sujeet Kulkarni

The goal of this project is to develop a beta version of the Glycoscience Educational Chatbot that can be deployed on a web server and evaluated by a pilot group of users. The student will analyze the strengths and limitations of the current alpha version and implement improvements that enhance usability, reliability, performance, and safety. Particular emphasis will be placed on improving the system&#39;s guardrails to ensure that responses remain focused on educational content, minimize hallucinations, and appropriately handle questions outside the scope of the knowledge base. The completed beta version will support formal user testing by researchers and

educators, providing valuable feedback for future development and broader deployment.

[[:File:GlyGen Volunteership (Fall 2026).pdf|Further information can be found here]]

==== 5. PredictMod Machine Learning (ML) Modeling Project ====
POC: Pat McNeely

Volunteers will conduct ML modeling using publicly-available -omics datasets that were previously identified (see our [[Recommended Publications for Intervention Outcome Prediction Models|Recommended Publications for IOPMs]] page). This volunteership will involve data harmonization, model training, and pipeline documentation.

Tasks associated with this project include:

# Exploring and understanding the data found in relevant PMIDs that can be used to train intervention outcome prediction models.
# Preparing the data for model training and model performance evaluation
# Testing the modeling tutorial, PredictMod platform, and associated project tools
# Documentation of the ML pipeline and testing results

Deliverables for this project include:

# ML-ready datasets & trained model scripts pushed to GitHub
# Pipeline documentation captured in BioCompute Objects (BCOs) and testing reports
# Volunteership documentation (final report, progress updates, symposium presentation)

Interested individuals should reach out to pmcneely@gwu.edu. Please note that this project requires attendance at biweekly meetings and a final presentation of your work.

==== 6. BiomarkerKB Biocuration Project ====
POC: Jeet Vora (primary), Maria Kim, Cyrus Au-Yeung

[https://biomarkerkb.org/about/ BiomarkerKB] is a biomedical knowledgebase project focused on harmonizing and structuring biomarker knowledge from scientific literature and public resources. We are currently recruiting individuals with experience working with LLMs (e.g. Claude, ChatGPT) to support the following tasks:

# '''Validation of existing published biomarkers from scientific literature (JV, MK, CA)'''
#* Review and validate previously reported biomarkers by checking the original literature, confirming evidence support, and standardizing biomarker annotations
#* Assess the evidence strength of biomarkers and identify additional literature to strengthen the support for biomarker claims
# '''Curation of novel biomarkers from scientific literature (MK)'''
#* Curate high-quality biomarkers for a selected disease area, organize the findings into a structured dataset
#* Standardize biomarker representations using controlled vocabularies and ontologies and classify biomarkers by their biomarker types
#* Construct and test-query a disease-specific biomarker knowledge graph (optional)
# '''Electronic Health Records Normal Entity Data Integration (JV)'''
#* Identify relevant EHR data elements (lab tests, diagnoses, procedures)
#* Map entities to standard terminologies (e.g., SNOMED CT, LOINC, ICD codes)
#* Resolve ambiguities and inconsistencies in mapping, clinical terminology
# '''Front-end testing for BiomarkerKB.org (MK, JV)'''
#* Test the BiomarkerKB web interface for functionality and data presentation, and document issues / improvement suggestions for the development team
# '''Benchmarking and LLM-based biomarker extraction (optional*) (CA)'''
#* Construct manually curated biomarker reference sets in the glycobiology domain to support benchmarking of LLM-based knowledge extraction pipelines.
#* Apply an LLM workflow to extract disease-specific biomarkers from literature and comparing model outputs against the manually curated benchmark sets

''Note:'' Participation in the benchmarking and LLM-based biomarker extraction subproject depends on sufficient progress in either task 1 or task 2. Volunteers are expected to first complete either validation of an LLM-extracted glycobiology subset or comprehensive curation of a disease-specific biomarker set before beginning this component. Because this volunteership is structured around a 20-hour-per-week commitment, participation in this part is not guaranteed.

Individuals interested in this opportunity may reach out to Jeet Vora ([mailto:jeetvora@gwu.edu jeetvora@gwu.edu]) for project details.
----

=== Requirements for Completion ===
'''Note:''' The following are mandatory. Failure to complete any will result in an incomplete volunteer record.

==== Documentation ====
All volunteers must maintain adequate documentation of their work, including written protocols and scripts submitted to GitHub.

==== Written Report ====
Submit a 1–2 page summary of your tasks and accomplishments to the Admin during the final week of your program.

==== Presentation & Slide Submission ====
Present your work last week of the 9-week period.

Slides must be submitted to the POCs.
----

=== Completion Certificate ===
A certificate of completion and a letter of recommendation will be provided to all participants who successfully complete the program. Additional recognition will be given to the top three volunteers with exceptional presentations at the end of the program.
----

=== Contact ===
mazumder_lab@gwu.edu.
----'''Volunteers'''

<nowiki>*</nowiki>Returning volunteer.

<sup>†</sup>GW Masters Degree Student

<sup>‡</sup>Not directly involved in the semester curriculum; long-term volunteer.

== Spring 2027 Symposium ==
The Summer symposium will be held virtually. '''Date:''' TBD

'''Time:''' TBD

'''Zoom Link''' - TBA

=== Agenda (All times are in Eastern Standard Time) ===
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Projects

2026-10-02T22:11:06Z

JewelDias:

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<h3>[https://hive.biochemistry.gwu.edu/dna.cgi?cmd=main The High-performance Integrated Virtual Environment (HIVE) platform]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
HIVE is a cloud-based environment optimized for the storage and analysis of extra-large data, such as biomedical data, clinical data, next-generation sequencing (NGS) data, mass spectrometry files, confocal microscopy images, post-market surveillance data, medical recall data, and many others. HIVE provides secure web access for authorized users to deposit, retrieve, annotate and compute on Big Data, and analyze the outcomes using web user interfaces. [https://docs.google.com/document/d/1F5iq00uKkJfdSsbwanvKOy-nPnwijH56mwbwa_HhzfY/edit?tab=t.0#heading=h.7dlfmngwfzih More here].

The HIVE platform and associated algorithms such as CensuScope and HIVE-Hexagon is used to support Metgenomics analysis infrastructure.<br><br>
[[GW-HIVE WIKI]]

[[METAGENOMICS WIKI]]

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<h3>[https://data.argosdb.org/ FDA-ARGOS Project (Food and Drug Administration-dAtabase for Regulatory-Grade micrObial Sequences)]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
The FDA-ARGOS Project (Food and Drug Administration-dAtabase for Regulatory-Grade micrObial Sequences) is a collaborative effort to create a high-quality genomic database for identifying and characterizing microbial pathogens. Developed in partnership with the FDA, University of Maryland, and NCBI, the project provides regulatory-grade genomic data, crucial for public health and diagnostic use. Expanded in 2021 with support from GWU, Temple University, and Embleema, FDA-ARGOS aims to enhance infectious disease research through rigorous quality control protocols. The ArgosDB hosts this data, offering downloadable sequences and reproducible workflows for research and regulatory applications.[https://www.fda.gov/medical-devices/science-and-research-medical-devices/database-reference-grade-microbial-sequences-fda-argos More here].<br><br>
[[FDA-ARGOS WIKI]]
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<h3>[https://www.biocomputeobject.org/ BioCompute Objects (BCO)]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
The BioCompute is FDA funded project to establish a framework for community-based development of standards for harmonization of High-throughput Sequencing (HTS), standardization of data formats, promotion of interoperability, and bioinformatics verification protocols. The BioCompute Object (BCO) was developed in the High-throughput Sequencing Computational Standards for Regulatory Sciences (HTS-CSRS) initiative in the BioCompute Objects Portal (BOP), a web portal to serve as a collaborative ground to encourage a dialogue to facilitate interoperability between different bioinformatic pipelines, industries, and developers. HIVE capabilities have been leveraged to support the development of the BCO. The BCO is versatile and adaptable to other common HTS analysis platforms. [https://docs.google.com/document/d/1WQFZm_PFiQXob4NyOKq6y-2ywnbmNoFHSS27fYf3l4Y/edit?tab=t.0#heading=h.bs8eki17tykx More here].<br><br>
[https://wiki.biocomputeobject.org/Main_Page BIOCOMPUTE OBJECTS WIKI]
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<h3>[https://www.glygen.org/ GlyGen]</h3>
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GlyGen (gly-glycobiology; gen-information), [https://www.glygen.org/<nowiki>] is an advanced glycoinformatics resource developed to facilitate discovery in basic and translational glycobiology research along with enhancing the integration of multidisciplinary information from diverse resources. GlyGen includes knowledge about molecular, biophysical and functional properties of glycans, genes, and proteins organized in pathways and ontologies, plus a rapidly growing body of biological big data related to cancer mutation and expression. GlyGen adopts an innovative user-driven approach for implementing, prioritizing and knowledge disseminating tools to address the questions and needs of glycobiology community. GlyGen is funded by the National Institute of General Medical Sciences under the grant # 1R24GM146616 - 01 and the National Institutes of Health Office of Strategic Coordination - The Common Fund under the grant # 1OT2OD032092. More information about GlyGen - </nowiki>https://www.glygen.org/about/ <br><br>
[https://wiki.glygen.org/Main_Page GlyGen WIKI]
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<h3>[https://hivelab.biochemistry.gwu.edu/predictmod PredictMod]</h3>
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PredictMod is an application designed to predict the outcome of an intervention prior to a patient initiating treatment. Our goal is to provide clinicians with a powerful decision making tool that enhances clinical understanding of patient-level data. The PredictMod platform utilizes machine learning tools and complex datasets based on electronic health records, gut microbiome, and -omics data to forecast patient outcomes, often in response to treatment for a particular condition. While our primary condition of interest is Prediabetes, the tool is designed to be used for a variety of conditions, interventions, and data types. <br> <br>
[https://hivelab.biochemistry.gwu.edu/wiki/PredictMod PredictMod WIKI]
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<h3>[[GW-FEAST]]</h3>
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The GW Federated Ecosystems for Analytics and Standardized Technologies (GW-FEAST) project is part of the ARPA-H FEAST performer team initiative that includes academic and industry partners. The goal of the ARPA-H performer teams is “to create bridges across data silos to make health data more accessible and usable”. <br><br>
[https://hivelab.biochemistry.gwu.edu/wiki/GW-FEAST GW-FEAST WIKI]
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<h3>[https://biomarkerkb.org/ Biomarker Knowledgebase]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
The Biomarker Partnership is a CFDE sponsored project to develop a knowledgebase that will organize and integrate biomarker data from different public sources. The data will be connected to contextual information to show a novel systems-level view of biomarkers. The motivation for this project is to improve the harmonization and organization of biomarker data. This will be done by mapping biomarkers from public sources to, and across, CF data elements. This mapping will bridge knowledge across multiple DCCs and biomedical disciplines.<br><br>
[https://wiki.biomarkerkb.org/Main_Page BioMarkerKB WIKI]
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<div style="font-size:160%; padding:.1em;">Volunteership Semesters</div>[[Volunteership Spring 2027]]
[[Volunteership Fall 2026]]
[[Volunteership Summer 2026]]

[[Volunteership Spring 2026]]

[[Volunteership Fall 2025]]

[[Volunteership 2025|Volunteership Summer 2025]]
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<h3>[https://hivelab.tst.biochemistry.gwu.edu/gfkb Gut Microbiome Analytic System (Microbiome)]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
The HIVE team received NSF funding to develop a Gut Microbiome Monitoring System (GutFeeling) as a tool which when used over time will allow users to rectify their dietary (such as consumption of probiotics and prebiotics) and other lifestyle habits and to help restore their normal microbiome. Rapid analysis of the large amount of metagenomic data, a major bottleneck, has been resolved by our group through the development of a novel algorithm and accompanying software called CensuScope. Through analysis of healthy gut microbiome data, we are actively developing a Knowledge Base (GutFeelingKB) to provide a clearer picture of not only an ideal personalized microbiome but also establish baseline characteristics for each customer. The Mazumder Lab is collaborating with the Milken School of Public Health and Kamtek Sequencing Facility to investigate the relationship between bacterial species commonly present in the digestive tract, diet, physical activity, lifestyle habits, and metabolic risk factors. [https://docs.google.com/document/d/18WyVTJrrf-FR0sHt634vO8Lwel-4OQxP9sNar7gYYro/edit?tab=t.0#heading=h.7qbm3f7lky31 More here].
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<h3>HIVE-EQAPOL Project on HIVE NGS Data Processing and Analysis</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
For this project, our group works closely with the External Quality Assurance Program Oversight Laboratory (EQAPOL) team to conduct HIV NGS data analysis and collaborate in terms of analyzing, storing, and tracking HIV NGS Data. Reliable identification of strains is critical for developing new assays, validating assay platforms, assisting regulators to evaluate test kits, monitoring HIV drug resistance, and informing vaccine development. The HIVE tools and platform are used for virus identification, recombination analysis, and clone discovery.
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<h3>[https://www.oncomx.org/ OncoMX]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
The OncoMX mission is to create an integrated cancer mutation and expression resource for exploring cancer biomarkers. OncoMX is a collaboration between the George Washington University (GW), NASA's Jet Propulsion Laboratory (JPL), the Swiss Institute of Bioinformatics (SIB), and the University of Delaware (UD). The core knowledgebase of OncoMX is derived from BioMuta and BioXpress integrated cancer mutation and expression databases which are actively maintained. Normal expression data from Bgee and custom text mining software augment the cancer data to improve functional interpretation of the reported variants and expression profiles. All data are wrapped into the OncoMX database and web portal, mapped to additional functional information from NCI Early Detection Research Network (EDRN) and Reactome. It is expected that the large-scale integration of cancer data and supporting information, provided by OncoMX with direct community feedback, will benefit cancer research by improving synthesis of information and may make earlier detection a reality.
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<h3>[https://hive.biochemistry.gwu.edu/dna.cgi?cmd=main Glycoproteomics Characterization Workflow and Data-Analysis Pipeline for Vaccines and Biosimilars]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
In this FDA funded project we are extending High-performance Integrated Virtual Environment (HIVE) capabilities through the development and integration of software tools and datasets for comparative analysis of glycoproteins. Glycomic analysis has many angles and has been extensively reviewed in recent literature. We propose to rely on the independent development of the glycomics field and incorporate these approaches in the HIVE pipeline as they mature while we develop a standardized glycoinformatics pipeline that will benefit investigators and regulators at the FDA.
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<h3>[[Tool Resources]]</h3>
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    '''''Main article:''' [[Tool Resources]]''<br>There are a variety of bioinformatic tool resources developed by our team.
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<h3>[[Dataset Resources]]</h3>
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    '''''Main article:''' [[Dataset Resources]]''<br>There are a variety of bioinformatic dataset resources integrated by our team.
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Projects

2026-10-02T22:10:47Z

JewelDias:

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<h3>[https://hive.biochemistry.gwu.edu/dna.cgi?cmd=main The High-performance Integrated Virtual Environment (HIVE) platform]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
HIVE is a cloud-based environment optimized for the storage and analysis of extra-large data, such as biomedical data, clinical data, next-generation sequencing (NGS) data, mass spectrometry files, confocal microscopy images, post-market surveillance data, medical recall data, and many others. HIVE provides secure web access for authorized users to deposit, retrieve, annotate and compute on Big Data, and analyze the outcomes using web user interfaces. [https://docs.google.com/document/d/1F5iq00uKkJfdSsbwanvKOy-nPnwijH56mwbwa_HhzfY/edit?tab=t.0#heading=h.7dlfmngwfzih More here].

The HIVE platform and associated algorithms such as CensuScope and HIVE-Hexagon is used to support Metgenomics analysis infrastructure.<br><br>
[[GW-HIVE WIKI]]

[[METAGENOMICS WIKI]]

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<h3>[https://data.argosdb.org/ FDA-ARGOS Project (Food and Drug Administration-dAtabase for Regulatory-Grade micrObial Sequences)]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
The FDA-ARGOS Project (Food and Drug Administration-dAtabase for Regulatory-Grade micrObial Sequences) is a collaborative effort to create a high-quality genomic database for identifying and characterizing microbial pathogens. Developed in partnership with the FDA, University of Maryland, and NCBI, the project provides regulatory-grade genomic data, crucial for public health and diagnostic use. Expanded in 2021 with support from GWU, Temple University, and Embleema, FDA-ARGOS aims to enhance infectious disease research through rigorous quality control protocols. The ArgosDB hosts this data, offering downloadable sequences and reproducible workflows for research and regulatory applications.[https://www.fda.gov/medical-devices/science-and-research-medical-devices/database-reference-grade-microbial-sequences-fda-argos More here].<br><br>
[[FDA-ARGOS WIKI]]
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<h3>[https://www.biocomputeobject.org/ BioCompute Objects (BCO)]</h3>
<div style="border-top: 1px solid #CCC; padding-top: 0.5em;">
The BioCompute is FDA funded project to establish a framework for community-based development of standards for harmonization of High-throughput Sequencing (HTS), standardization of data formats, promotion of interoperability, and bioinformatics verification protocols. The BioCompute Object (BCO) was developed in the High-throughput Sequencing Computational Standards for Regulatory Sciences (HTS-CSRS) initiative in the BioCompute Objects Portal (BOP), a web portal to serve as a collaborative ground to encourage a dialogue to facilitate interoperability between different bioinformatic pipelines, industries, and developers. HIVE capabilities have been leveraged to support the development of the BCO. The BCO is versatile and adaptable to other common HTS analysis platforms. [https://docs.google.com/document/d/1WQFZm_PFiQXob4NyOKq6y-2ywnbmNoFHSS27fYf3l4Y/edit?tab=t.0#heading=h.bs8eki17tykx More here].<br><br>
[https://wiki.biocomputeobject.org/Main_Page BIOCOMPUTE OBJECTS WIKI]
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<h3>[https://www.glygen.org/ GlyGen]</h3>
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GlyGen (gly-glycobiology; gen-information), [https://www.glygen.org/<nowiki>] is an advanced glycoinformatics resource developed to facilitate discovery in basic and translational glycobiology research along with enhancing the integration of multidisciplinary information from diverse resources. GlyGen includes knowledge about molecular, biophysical and functional properties of glycans, genes, and proteins organized in pathways and ontologies, plus a rapidly growing body of biological big data related to cancer mutation and expression. GlyGen adopts an innovative user-driven approach for implementing, prioritizing and knowledge disseminating tools to address the questions and needs of glycobiology community. GlyGen is funded by the National Institute of General Medical Sciences under the grant # 1R24GM146616 - 01 and the National Institutes of Health Office of Strategic Coordination - The Common Fund under the grant # 1OT2OD032092. More information about GlyGen - </nowiki>https://www.glygen.org/about/ <br><br>
[https://wiki.glygen.org/Main_Page GlyGen WIKI]
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<h3>[https://hivelab.biochemistry.gwu.edu/predictmod PredictMod]</h3>
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PredictMod is an application designed to predict the outcome of an intervention prior to a patient initiating treatment. Our goal is to provide clinicians with a powerful decision making tool that enhances clinical understanding of patient-level data. The PredictMod platform utilizes machine learning tools and complex datasets based on electronic health records, gut microbiome, and -omics data to forecast patient outcomes, often in response to treatment for a particular condition. While our primary condition of interest is Prediabetes, the tool is designed to be used for a variety of conditions, interventions, and data types. <br> <br>
[https://hivelab.biochemistry.gwu.edu/wiki/PredictMod PredictMod WIKI]
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<h3>[[GW-FEAST]]</h3>
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The GW Federated Ecosystems for Analytics and Standardized Technologies (GW-FEAST) project is part of the ARPA-H FEAST performer team initiative that includes academic and industry partners. The goal of the ARPA-H performer teams is “to create bridges across data silos to make health data more accessible and usable”. <br><br>
[https://hivelab.biochemistry.gwu.edu/wiki/GW-FEAST GW-FEAST WIKI]
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<h3>[https://biomarkerkb.org/ Biomarker Knowledgebase]</h3>
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The Biomarker Partnership is a CFDE sponsored project to develop a knowledgebase that will organize and integrate biomarker data from different public sources. The data will be connected to contextual information to show a novel systems-level view of biomarkers. The motivation for this project is to improve the harmonization and organization of biomarker data. This will be done by mapping biomarkers from public sources to, and across, CF data elements. This mapping will bridge knowledge across multiple DCCs and biomedical disciplines.<br><br>
[https://wiki.biomarkerkb.org/Main_Page BioMarkerKB WIKI]
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<div style="font-size:160%; padding:.1em;">Volunteership Semesters</div>[[Volunteership Spring 2027]][[Volunteership Fall 2026]]
[[Volunteership Summer 2026]]

[[Volunteership Spring 2026]]

[[Volunteership Fall 2025]]

[[Volunteership 2025|Volunteership Summer 2025]]
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<div style="font-size:160%; padding:.1em;">Past Projects</div>
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<h3>[https://hivelab.tst.biochemistry.gwu.edu/gfkb Gut Microbiome Analytic System (Microbiome)]</h3>
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The HIVE team received NSF funding to develop a Gut Microbiome Monitoring System (GutFeeling) as a tool which when used over time will allow users to rectify their dietary (such as consumption of probiotics and prebiotics) and other lifestyle habits and to help restore their normal microbiome. Rapid analysis of the large amount of metagenomic data, a major bottleneck, has been resolved by our group through the development of a novel algorithm and accompanying software called CensuScope. Through analysis of healthy gut microbiome data, we are actively developing a Knowledge Base (GutFeelingKB) to provide a clearer picture of not only an ideal personalized microbiome but also establish baseline characteristics for each customer. The Mazumder Lab is collaborating with the Milken School of Public Health and Kamtek Sequencing Facility to investigate the relationship between bacterial species commonly present in the digestive tract, diet, physical activity, lifestyle habits, and metabolic risk factors. [https://docs.google.com/document/d/18WyVTJrrf-FR0sHt634vO8Lwel-4OQxP9sNar7gYYro/edit?tab=t.0#heading=h.7qbm3f7lky31 More here].
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<h3>HIVE-EQAPOL Project on HIVE NGS Data Processing and Analysis</h3>
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For this project, our group works closely with the External Quality Assurance Program Oversight Laboratory (EQAPOL) team to conduct HIV NGS data analysis and collaborate in terms of analyzing, storing, and tracking HIV NGS Data. Reliable identification of strains is critical for developing new assays, validating assay platforms, assisting regulators to evaluate test kits, monitoring HIV drug resistance, and informing vaccine development. The HIVE tools and platform are used for virus identification, recombination analysis, and clone discovery.
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<h3>[https://www.oncomx.org/ OncoMX]</h3>
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The OncoMX mission is to create an integrated cancer mutation and expression resource for exploring cancer biomarkers. OncoMX is a collaboration between the George Washington University (GW), NASA's Jet Propulsion Laboratory (JPL), the Swiss Institute of Bioinformatics (SIB), and the University of Delaware (UD). The core knowledgebase of OncoMX is derived from BioMuta and BioXpress integrated cancer mutation and expression databases which are actively maintained. Normal expression data from Bgee and custom text mining software augment the cancer data to improve functional interpretation of the reported variants and expression profiles. All data are wrapped into the OncoMX database and web portal, mapped to additional functional information from NCI Early Detection Research Network (EDRN) and Reactome. It is expected that the large-scale integration of cancer data and supporting information, provided by OncoMX with direct community feedback, will benefit cancer research by improving synthesis of information and may make earlier detection a reality.
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<h3>[https://hive.biochemistry.gwu.edu/dna.cgi?cmd=main Glycoproteomics Characterization Workflow and Data-Analysis Pipeline for Vaccines and Biosimilars]</h3>
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In this FDA funded project we are extending High-performance Integrated Virtual Environment (HIVE) capabilities through the development and integration of software tools and datasets for comparative analysis of glycoproteins. Glycomic analysis has many angles and has been extensively reviewed in recent literature. We propose to rely on the independent development of the glycomics field and incorporate these approaches in the HIVE pipeline as they mature while we develop a standardized glycoinformatics pipeline that will benefit investigators and regulators at the FDA.
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<div style="font-size:160%; padding:.1em;">RESOURCES</div>
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<h3>[[Tool Resources]]</h3>
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    '''''Main article:''' [[Tool Resources]]''<br>There are a variety of bioinformatic tool resources developed by our team.
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<h3>[[Dataset Resources]]</h3>
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    '''''Main article:''' [[Dataset Resources]]''<br>There are a variety of bioinformatic dataset resources integrated by our team.
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