Avi Ma'ayan

Avi Ma'ayan, PhD

About Me

Dr. Ma’ayan is a Mount Sinai Endowed Professor in Bioinformatics, Professor in the Department of Pharmacological Sciences, Director of the Mount Sinai Center for Bioinformatics, and a faculty member of the Icahn Genomics Institute. Dr. Ma'ayan is also Principal Investigator of the NIH-funded Mount Sinai Knowledge Management Center for Illuminating the Druggable Genome and Mount Sinai Proteogenomic Data Analysis Center. The Ma'ayan Laboratory applies computational and mathematical methods to study the complexity of regulatory networks in mammalian cells. His research team 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. The Ma'ayan Laboratory 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.

Avi Ma'ayan's Publications on PubMed | Google Scholar | ResearchGate

Ma'ayan Laboratory website

Featured Software Tools Developed by the Ma'ayan Laboratory:

For a complete list of our software tools, databases and datasets, please visit our Resources page.

NIH-funded Centers:

In the News:

PROFESSOR | Pharmacological Sciences
Research Topics

Addiction, Aging, Bioinformatics, Biomedical Sciences, Biostatistics, Cancer, Computational Biology, Diabetes, Drug Design and Discovery, Gene Expressions, Gene Regulation, Genetics, Genomics, Kidney, Mass Spectrometry, Mathematical Modeling of Biomedical Systems, Mathematical and Computational Biology, Personalized Medicine, Pharmacogenomics, Pharmacology, Protein Complexes, Protein Kinases, Proteomics, Reprogramming, Signal Transduction, Stem Cells, Systems Biology, Systems Pharmacology, Technology & Innovation, Theoretical Biology, Transcription Factors, Viruses and Virology

Multi-Disciplinary Training Areas

Artificial Intelligence and Emerging Technologies in Medicine [AIET], Disease Mechanisms and Therapeutics (DMT), Genetics and Genomic Sciences [GGS]