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Avi Ma'ayan

Avi Ma'ayan, PhD

About Me

Dr. Ma’ayan is a Mount Sinai Endowed Professor in Bioinformatics, Director of the Mount Sinai Center for Bioinformatics, Professor in the Department of Pharmacological Sciences, Professor in the Department of Artificial Intelligence and Human Health, and faculty member of the Icahn Genomics Institute. Dr. Ma'ayan is also a Principal Investigator of the NIH Common Fund Data Resource Center (DRC) for the Common Fund Data Ecosystem (CFDE), a NCI-funded ITCR resource center, a NIDDK-funded diabetes hypothesis platform, and the NCI-funded Mount Sinai Proteogenomic Data Analysis Center. The Ma'ayan Laboratory applies computational methods to study the inner workings 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 bioinformatics software applications to enable experimental biologists to form novel hypotheses from high-throughput omics datasets, while aiming to better understand the structure and function of regulatory networks in mammalian cellular and multi-cellular complex 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 bioinformatics software applications developed by the Ma'ayan Lab, please visit the Resources page.

NIH-funded Centers:

In the News:

Language
English
Position
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]