Summary of Research Interests
The Ma’ayan Laboratory develops computational and mathematical methods to study the complexity of regulatory networks in mammalian cells. We apply 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. We develop 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. Below are some of the software tools we designed and developed recently:
Gene-List Enrichment Analysis Tool
An integrative web-based and mobile gene list enrichment analysis tool providing various types of visualization summaries of collective functions of gene lists.
Browser Extension for Extracting Differentially Expressed Gene Sets from GEO
A browser extension and web application to extract gene sets from GEO and analyze these lists for common biological functions.
Crowd Extracted Expression of Differential Signatures
Collections of processed gene, drug and disease signatures from GEO.
L1000 Characteristic Direction Signature Search Engine
Queries gene expression signatures against the LINCS L1000 to identify and prioritize small molecules that can reverse or mimic the observed input expression pattern.
For a complete list of our software tools, databases and datasets please visit our Resources page. We apply these and other computational methods for the analysis of a variety of collaborative projects. The results from our analyses produce concrete suggestions and predictions for further functional experiments. The predictions are tested by our collaborators and our analyses methods are delivered as software tools and databases for the systems biology research community.