Prof. Noam Shomron

Prof. Noam Shomron

Research work

Professor Noam Shomron is passionate about using basic science to advance better healthcare. Prof Shomron heads the Functional Genomic Team at the Faculty of Medicine at Tel Aviv University, after training at MIT. He leads a multidisciplinary team of scientists that develops computational methods for parsing big-data in the bio-medical field using Artificial Intelligence. Shomron’s aim is to deepen our understanding of diseases in order to translate information into clinical reality. Shomron is also the Director of Djerassi Institute of Oncology; Editor of ‘Deep Sequencing Data Analysis’ book (Springer, Edition I and II); Director of ‘Rare-Genomics’ Israel (NPO); Academic Director of ‘ScienceAbroad’ (NPO); and, Co-founder and Chief Scientific Officer (CSO) of Variantyx which provides clinical interpretation of whole genome sequences. 
TEDx talks:

Areas of interest & scientific knowledge

Cellular & Molecular Neuroscience

Selected Publications
  • Predicting bloodstream infection outcome using machine learning. Zoabi Y, Kehat O, Lahav D, Weiss-Meilik A, Adler A, Shomron N. Sci Rep. 2021 Oct 11;11(1):20101. doi: 10.1038/s41598-021-99105-2. PMID: 34635696 
  • Genome wide analysis implicates upregulation of proteasome pathway in major depressive disorder. Belaish S, Israel-Elgali I, Shapira G, Krieger I, Segev A, Nitzan U, Majer M, Bloch Y, Weizman A, Gurwitz D, Shomron N, Hertzberg L. Transl Psychiatry. 2021 Jul 28;11(1):409. doi: 10.1038/s41398-021-01529-x. PMID: 34321460 
    Blood transcriptional response to treatment-resistant depression during electroconvulsive therapy. Israel-Elgali I, Hertzberg L, Shapira G, Segev A, Krieger I, Nitzan U, Bloch Y, Pillar N, Mayer O, Weizman A, Gurwitz D, Shomron N. J Psychiatr Res. 2021 Sep;141:92-103. doi: 10.1016/j.jpsychires.2021.06.039. Epub 2021 Jun 22. PMID: 34182381
  • Machine learning-based prediction of COVID-19 diagnosis based on symptoms. Zoabi Y, Deri-Rozov S, Shomron N. NPJ Digit Med. 2021 Jan 4;4(1):3. doi: 10.1038/s41746-020-00372-6. PMID: 33398013 
  • Bayesian-based noninvasive prenatal diagnosis of single-gene disorders. Rabinowitz T, Polsky A, Golan D, Danilevsky A, Shapira G, Raff C, Basel-Salmon L, Matar RT, Shomron N. Genome Res. 2019 Mar;29(3):428-438. doi: 10.1101/gr.235796.118. Epub 2019 Feb 20. PMID: 30787035
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