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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L1000 fireworks display (L1000FWD) is a web application that provides interactive visualization of over 16,000 drug and small-molecule induced gene expression signatures. L1000FWD enables coloring of signatures by different attributes such as cell type, time point, concentration, as well as drug attributes such as MOA and clinical phase. Signature similarity search is implemented to enable the search for mimicking or opposing signatures given as input of up and down gene sets. Each point on the L1000FWD interactive map is linked to a signature landing page, which provides multifaceted knowledge from various sources about the signature and the drug. Read More
Wang Z, Lachmann A, Keenan AB, Ma’ayan A. L1000FWD: Fireworks visualization of drug-induced transcriptomic signatures. Bioinformatics bty060 (2018).