Computational and Mathematical Methods to Study the Complexity of Regulatory Networks in Mammalian Cells

The Ma’ayan Laboratory applies graph-theory algorithms, machine-learning techniques and dynamical modeling to study how intracellular regulatory systems function as networks to control cellular processes such as differentiation, apoptosis and proliferation.

Our research team develops software systems to help experimental biologists form novel hypotheses from high-throughput data, and develop theories about the structure and function of regulatory networks in mammalian systems. Read More

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Crowdsourcing for Scientific Discovery: Mount Sinai Researchers Find Novel Ways to Analyze Data for Drug and Target Discovery

DCIC_Lightning_Talk_WangResearchers in the Ma’ayan Laboratory have crowdsourced the annotation and analysis of a large number of gene expression profiles from the Gene Expression Omnibus (GEO). More than 70 volunteers from 25 countries helped the team analyze the data, enabling the identification of new associations between genes, diseases, and drugs. This study was published in the journal Nature Communications.

Read the full press release here.

Citation: Wang et al. Extraction and analysis of signatures from the Gene Expression Omnibus by the crowdNature Communications 2016 Sep 26;7:12846.