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

 Featured Publications

• L1000CDS2: LINCS L1000 Characteristic Direction Signatures Search Engine
• An Open RNA-Seq Data Analysis Pipeline Tutorial with an Example of Reprocessing Data from a Recent Zika Virus Study
• The Harmonizome: A Collection of Processed Datasets Gathered to Serve and Mine Knowledge about Genes and Proteins
• Enrichr: A Comprehensive Gene Set Enrichment Analysis Web Server 2016 Update
• Drug-induced Adverse Events Prediction with the LINCS L1000 Data

L1000CDS2: LINCS L1000 Characteristic Direction Signatures Search Engine