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

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 Featured Publications

• Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd. Nature Communications 7:12846.
• GEN3VA: aggregation and analysis of gene expression signatures from related studies. BMC Bioinformatics 17(1):461.
• The harmonizome: a collection of processed datasets gathered to serve and mine knowledge about genes and proteins. Database (Oxford) pii: baw100.
• Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Research 44(W1):W90-7.