Rummagene and Rummageo: Automated Mining of Gene Sets from PubMed Central (PMC) and the Gene Expression Omnibus (GEO)

Data Science Seminar Series

January 24, 2024 | 11:00 AM – 12:00 PM

Virtual

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In this seminar, you’ll learn about Rummagene and Rummageo, two web-based tools developed by researchers in the Ma’ayan Lab, Icahn School of Medicine, at Mount Sinai in New York.

Dr. Avi Ma’ayan will show how you can use these tools to access hundreds of thousands of gene sets. You’ll learn about:

• Rummagene: A tool that lets you access human and mouse gene sets from the supporting materials in PubMed Central (PMC). To date, researchers have used this application to scan 5,670,312 PMC articles, uncovering 126,390 publications with 667,029 gene sets.
• Rummageo: A tool that gives you access to gene sets from human and mouse RNA-sequencing studies in the Gene Expression Omnibus (GEO) database. Rummageo currently contains 135,264 human and 158,062 mouse gene sets from 23,395 GEO studies.

Don’t miss this opportunity to learn from Dr. Ma’ayan. His lab focuses on developing web-based bioinformatics software tools and databases to help us better understand important cellular events, such as cell differentiation, growth, and death, and how these processes link to gene expression (i.e., to identify networks, pathways, and possible targets for therapy). To date, more than 3 million people have used these bioinformatics tools.

About the Speaker

Avi Ma’ayan, Ph.D.
Dr. Ma’ayan is the director of the Mount Sinai Center for Bioinformatics and a professor in the Department of Pharmacological Sciences.

About the Data Science Seminar Series

CBIIT’s Data Science Seminar Series is dedicating its 2026 events to spotlighting the use of AI in cancer research and care. Brought to you by CBIIT and NCI's Division of Cancer Treatment and Diagnosis AI working group, the upcoming webinars will explore a variety of questions, such as the following:

• How can AI be used for diagnosis, treatment, or omics research?
• What are the related laws and ethical considerations for AI?
• How can we empower an AI-ready cancer research community through workforce development, collaborations, and funding?

To view upcoming speakers or recordings of past presentations, visit the Data Science Seminar Series page.