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<div style="font-size:290%; padding:.1em; text-align: center;">[https:// | <div style="font-size:290%; padding:.1em; text-align: center;">[https://hivelab.biochemistry.gwu.edu/ Welcome] to the HIVE Lab (Mazumder Research Group) Wiki</div><br> | ||
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<div style="font-size:100%;">The HIVE Lab group is involved in developing the High-performance Integrated Virtual Environment (HIVE) which is a collaborative project between the CBER Food and Drug Administration (FDA) and Dr. Raja Mazumder's team at The George Washington University (GW). This effort aims to integrate various high throughput data analysis tools into the HIVE platform. | <div style="font-size:100%;">The HIVE Lab group is involved in developing the High-performance Integrated Virtual Environment (HIVE) which is a collaborative project between the CBER Food and Drug Administration (FDA) and Dr. Raja Mazumder's team at The George Washington University (GW). This effort aims to integrate various high throughput data analysis tools into the HIVE platform. | ||
In addition to the HIVE platform, the group is involved in developing standards for bioinformatics communication via BioCompute Objects, knowledgebases for glycoinformatics (GlyGen), cancer research (BiomarkerKB, OncoMX, BioMuta, BioXpress), and microbiome analysis via the GutFeeling Knowledge Base (GFKB). The lab leverages knowledge graphs and advanced ML/AI technologies, including large language models, to harmonize, map, and uncover valuable insights from clinical data, omics datasets, knowledgebases, and scientific publications.</div>The lab manages several social media accounts dedicated to various projects.<br>GlyGen: [https://www.linkedin.com/company/glygen/ LinkedIn] | In addition to the HIVE platform, the group is involved in developing standards for bioinformatics communication via BioCompute Objects, knowledgebases for glycoinformatics (GlyGen), cancer research (BiomarkerKB, OncoMX, BioMuta, BioXpress), and microbiome analysis via the GutFeeling Knowledge Base (GFKB). The lab leverages knowledge graphs and advanced ML/AI technologies, including large language models, to harmonize, map, and uncover valuable insights from clinical data, omics datasets, knowledgebases, and scientific publications.</div>The lab manages several social media accounts dedicated to various projects.<br>GlyGen: [https://www.linkedin.com/company/glygen/ LinkedIn], [https://mstdn.science/@glygen Mastadon]; Bluesky | BioCompute: [https://www.linkedin.com/company/biocompute-partnership LinkedIn] | GW Bioinfo & Biochem students and alumni: [https://www.linkedin.com/groups/8313079/ LinkedIn]<div style="font-size:100%;">This wiki system provides complementary information to the [https://hivelab.biochemistry.gwu.edu/ HIVE Lab] and is divided into the following main sections:</div> | ||
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'''''Main article:''' [[Opportunities]]''<br>Interested in joining our team? Learn about our team. | '''''Main article:''' [[Opportunities]]''<br>Interested in joining our team? Learn about our team. | ||
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<h3>[[Events]]</h3> | |||
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'''''Main article:''' [[Events]]''<br>Interested in knowing about our events. | |||
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Latest revision as of 19:40, 3 December 2024
Welcome to the HIVE Lab (Mazumder Research Group) Wiki
Publications
Main article: Publications
The HIVE team has a variety of peer-reviewed publications, book chapters, posters, brochures, and multimedia available for the public.
Tool Resources
Main article: Tool Resources
There are a variety of bioinformatic tool resources developed by our team.
Dataset Resources
Main article: Dataset Resources
There are a variety of bioinformatic dataset resources integrated by our team.
Opportunities
Main article: Opportunities
Interested in joining our team? Learn about our team.
External links
- Official