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News Research Publications Resources Courses Team Positions Available Alumni Summer Program Virtual Symposium Contact Us Ma’ayan Laboratory, Computational Systems Biology icahn.mssm.edu / Inside Mount Sinai Blog Search Menu HomeNews Research Publications Resources Courses Team Positions Available Alumni Summer Program Virtual Symposium Contact Us Computational and Mathematical Methods to Study the Complexity of Regulatory Networks in Mammalian Cells The Ma’ayan Laboratory applies machine learning and other statistical mining techniques to study how intracellular regulatory systems function as networks to control cellular processes such as differentiation, dedifferentiation, apoptosis and proliferation. Our research team develops software systems to help experimental biologists form novel hypotheses from high-throughput data, while aiming to better understand the structure and function of regulatory networks in mammalian cellular and multi-cellular systems. Read More Featured Publication Rummagene: massive mining of gene sets from supporting materials of biomedical research publications Many biomedical research publications contain gene sets in their supporting tables, and these sets are currently not available for search and reuse. By crawling PubMed Central, the Rummagene server provides access to hundreds of thousands of such mammalian gene sets. These sets are served for enrichment analysis, free text, and table title search. Investigating statistical patterns within the Rummagene database, we demonstrate that Rummagene can be used for transcription factor and kinase enrichment analyses, and for gene function predictions. By combining gene set similarity with abstract similarity, Rummagene can find surprising relationships between biological processes, concepts, and named entities. Overall, Rummagene brings to surface the ability to search a massive collection of published biomedical datasets that are currently buried and inaccessible. The Rummagene web application is available at rummagene.com Citation: Clarke DJB, Marino GB, Deng EZ, Xie Z, Evangelista JE, Ma’ayan A. Rummagene: massive mining of gene sets from supporting materials of biomedical research publications . Communications Biology 2024 7(1):482. Mount Sinai Center for Bioinformatics Analyzing, visualizing, and mining data from omics studies for drug discovery Biomedical Big Data Science Training Summer Research Training Program Common Fund Data Ecosystem Data Resource Center for CFDE Featured Tools Appyters Apps to execute bioinformatics workflows Enrichr Integrative gene-list enrichment analysis MOOCs on Coursera Network Analysis in Systems Biology Enroll Now Big Data Science with LINCS Enroll...