Avi Ma'ayan, PhD
img_Avi Ma'ayan
PROFESSOR | Pharmacological Sciences
PROFESSOR | Artificial Intelligence and Human Health
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 Area
Artificial Intelligence and Emerging Technologies in Medicine [AIET], Disease Mechanisms and Therapeutics (DMT), Genetics and Genomic Sciences [GGS]
Systems Biology, Systems Pharmacology, Biomedical Big Data, Bioinformatics, Computational Biology, Data Mining, Software Engineering, Network Analysis, Artificial Intelligence

Research Team:
Program Director: Sherry Jenkins, MS
Research Assistant Professor: Alexander Lachmann, PhD
Data Scientist: Daniel Clarke, MS
Bioinformatician: John Erol Evangelista, MS
Bioinformatics Software Engineers: Nasheath Ahmed, BS, AB; Anna Byrd, MEng; Ido Diamant, BS; Giacomo Marino, ScB, AB
Systems Analyst: Heesu Kim, MBA, MS
2024 Undergrad and Post-bac Research Trainees: Bilal Ali, Eugenia Ampofo BA, Andrew Chung, Sophie Gideon, Eric Lee, Kareena Legare, Nathania Lingam, Tejal Nair, Lucas Sasaya, Andrew Stein

Summary of Research Studies:

Largest and Most Diverse Collection of Annotated Gene Sets
Gene set enrichment analysis is central to many biological and biomedical projects that measure mRNA and protein expression at the whole-genome scale. Gene set enrichment analysis is typically limited to few literature-base background knowledge libraries such as those created from the Gene Ontology and from pathway databases such as KEGG, WikiPathways, and Reactome. We have demonstrated that enrichment analysis can be expanded to using data from many other biological domains. For developing the tools Enrichr, Enrichr-KG, Rummagene, Rummageo, kinase enrichment analysis (KEA), ChIP-seq enrichment analysis (ChEA), and Harmonizome, we have integrated data from many key biomedical resources into useful gene set libraries. These libraries better inform enrichment analyses from omics studies. So far, over 2 million unique users used these bioinformatics software applications with a current rate of ~4,000 unique users per day.

Original Methods to Identify Differentially Expressed Genes, Perform Gene Set Enrichment Analyses, and Benchmark these Data Analysis Methods
One of the key statistical tests in the fields of transcriptomics is the identification of differentially expressed genes. We developed a multivariate method called the Characteristic Direction to better identify the “correct” differentially expressed genes. The Characteristic Direction method was extended to also perform improved enrichment analysis using a similar concept. Using a unique benchmarking strategy, we can objectively evaluate the Characteristic Direction method and many other leading methods for differential expression and enrichment analyses such as limma, GSEA and DESeq.

Translational Computational Research in Cancer and Kidney Disease
In collaboration with other experimental and computational biology laboratories, we have made great strides in the past several years in studying kidney disease, diabetes, HIV, and cancer. We have developed unique computational methods that led to the identification of potential targets and drugs for attenuating kidney fibrosis, diabetic kidney disease, and HIVAN. Our collaborative work also proposed treatment combinations for early-stage kidney disease intervention. These advances were possible by applying the unique algorithms that we developed which include: Expression2Kinases, SigCom LINCS, and TargetRanger.

Innovative Bioinformatics Software Infrastructure
To lower the barrier of entry for bioinformaticians and to streamline the development of bioinformatics software applications, we developed Appyters. With Appyters bioinformaticians can rapidly develop full-stack web-based bioinformatics applications from their Jupyter Notebook. Currently over 100 Appyters are available from the Appyters Catalog. For a CFDE Partnership project, our team developed the Playbook Workflow Builder, a platform that facilitates the visual dynamic construction of bioinformatics workflows. Along these efforts, we also created FAIRshake, a flexible framework for performing manual and automated evaluation of digital objects for adherence to defined community established standards.

For more information, please visit the Ma'ayan Laboratory website.

BSc, Fairleigh Dickinson University

MS, Fairleigh Dickinson University

PhD, Mount Sinai School of Medicine

2020

Mount Sinai Graduate School Alumni Award

Icahn School of Medicine at Mount Sinai

2013

Irma T. Hirschl Career Scientist Award

2011

Dr. Harold and Golden Lamport Research Award

Mount Sinai School of Medicine

2006

Doctoral Dissertation Award in the Graduate School of Biological Sciences

Mount Sinai School of Medicine

2006

Graduate School of Biological Sciences Award for Research Achievement

Mount Sinai School of Medicine

Faculty Spotlight: Avi Ma'ayan, PhD

Physicians and scientists on the faculty of the Icahn School of Medicine at Mount Sinai often interact with pharmaceutical, device, biotechnology companies, and other outside entities to improve patient care, develop new therapies and achieve scientific breakthroughs. In order to promote an ethical and transparent environment for conducting research, providing clinical care and teaching, Mount Sinai requires that salaried faculty inform the School of their outside financial relationships.

Below are financial relationships with industry reported by Dr. Ma'ayan during 2023 and/or 2024. Please note that this information may differ from information posted on corporate sites due to timing or classification differences.

Consulting or Other Professional Services Examples include, but are not limited to, committee participation, data safety monitoring board (DSMB) membership

  • ProtAI
  • Elucidata

Editorial Services

  • Wiley Publishing

Equity (Stock or stock options valued at greater than 5% ownership of a publicly traded company or equity of any value in a privately held company)

  • ProtAI
  • Elucidata

Mount Sinai's faculty policies relating to faculty collaboration with industry are posted on our website. Patients may wish to ask their physician about the activities they perform for companies.