Symposium 2025

The HIVE Lab summer symposium is scheduled for Thursday July 31, 2025. It is an exciting time for the lab volunteers and interns to present their findings on the projects they worked on for 8 weeks.

Program and Information and Registeration

Symposium Venue

The HIVE lab symposium will held in person at The George Washington University, Washington DC with an option to join virtually.

In Person - Ross 647, Ross Hall, School of Health and Medical Sciences, The George Washington University, Washington DC (MAP)

Virtual - Zoom (Click on the Link to register below)

Zoom Registration

Registration Link - https://gwu-edu.zoom.us/meeting/register/nziV1ZJQRt6V4ZOEfjpU_g

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Agenda

All times in Eastern Standard Time

Time (ET)	Project	Title	Presenter
10:00am	Welcome and Introduction		Michael Tiemeyer (10 min)
Group 1 Moderator : Nathan Edwards
10:10am	CFDE	Integrating Biocuration and Data Standardization to Generate Machine Learning-Ready Glycan Datasets	Ana Jaramillo and Yuxin Zou (20 min)
10:30am	CFDE	Machine Learning Models for Linkage Prediction in Glycan Images	Campbell Ross (15 min)
10:45am	CFDE	A Graph-Based AI Workflow for Mining Glycan Biomarkers and Related Annotations from Publications	Cyrus Chun Hong Au Yeung (15 min)
11:00am	BiomarkerKB	TBA	Sohana Bahl, Isaac Kim, Sparsh Gupta (15 min)
11:15am	BiomarkerKB	TBA	Nathan Ressom, Ana Vohralikova, Mathias Belay (15 min)
11:30am	BiomarkerKB	TBA	John McCaffery, Alma Ogunsina, Akale Kinfe (15 min)
11:45am	Open Q and A		All (30 min)
12:30pm	LUNCH (90 mins)
Group 2 Moderator : Rene Ranzinger
2:00pm	Predictmod AI-READI	Robust Classification of Glycemic Health States from Continuous Glucose	Nikhil Arethiya (15 min)
2:15pm	Predictmod Curation	PredictMod: PubMed Curation for Training an LLM for Recommendation	Grace Chong, Aaron Ressom, Diya Kamalabharathy (15 min)
2:30pm	Glycobiology Web Development	A Resource Drill Down and Visualization for the Glyspace Alliance	Diya Kamalabharathy (5 min)
2:35pm	Argos	Curation of Emerging Pathogen Genomes for FDA-ARGOS Database Expansion	Miao Wang (15 min)
2:50pm	GlyGen	GlyGen Biocuration Project	Aise Arpinar, Haravinay P. Gujjulla, Nahom Abel (20 min)
3:10pm	GlycoSiteMiner	TBA	(15 min)
3:25pm	Open Q and A | Closing Remarks		All (20 min) | Raja Mazumder

Project Description

CFDE Project

The CFDE project focuses on integrating biocuration and data standardization to generate machine learning-ready glycan datasets. It brings together curated information and structured metadata to ensure that glycan-related data is both interoperable and computationally accessible. As part of this effort, the project supports the development of machine learning models for linkage prediction in glycan images, enabling automated interpretation of glycan structures from visual representations. In addition, a graph-based AI workflow is being implemented to mine glycan biomarkers and related annotations from scientific publications, helping to uncover novel insights and associations. These approaches collectively advance the integration of glycobiology into broader biomedical research by making glycan data more usable for downstream AI applications.

GlyGen Project

The GlyGen Biocuration project focuses on integrating legacy, yet valuable, data from the CarbBank and CFG databases into the GlyGen infrastructure. A key challenge is mapping metadata, such as species names and publication references, to standardized dictionaries and ontologies. While most entries have been automatically matched using custom scripts, remaining inconsistencies, including outdated, misspelled, or abbreviated terms, require manual curation using resources such as Google, PubMed, and domain-specific dictionaries and ontologies.

BiomarkerKB Biocuration Project

The Biomarker Biocuration project focuses on biomarker curation from abstracts and publications in the BiomarkerKB data model. A key challenge in curating biomarkers is the vast amount of data that is present over various publications. Manual curation requires reading, inferring, and understanding key elements of biomarker data and being able to map it to the defined biomarker data model. LLM methodologies will help immensely in being able to recognize biomarker and condition data and being able to map information found into the data model while also automatically mapping other contextual and standardized data to the model to allow data to be AI andmachine leanring ready.

ArgosDB Curation Project

This project focuses on evaluating and curating high-quality genomes of emerging and clinically relevant pathogens, with an emphasis on fungal species. Using public genomic repositories and FDA-ARGOS inclusion criteria, I identify candidate organisms for database expansion to support diagnostic assay development and public health surveillance.