Yael  Mandel-Gutfreund

Yael Mandel-Gutfreund

Education/ Resume:

Professor, Technion-Israel Institute of Technology, Haifa

Betty Ann and Raymond J. Rosen chair in Life Sciences

Professor of Biology, Secondary affiliation in Computer Sciences

Dean, Faculty of Biology, Technion

Director of the Bioinformatics Knowledge Unit at the Technion

PhD,  1999, Hebrew University of Jerusalem,  Faculty of Medicine (Bioinformatics)

M.Sc. 1992 The Hebrew University of Jerusalem, Faculty of Medicine (Human Genetics)

BS.C, 1990, The Hebrew University of Jerusalem, Cum Laude (Biology, minor Chemistry)

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Research Summary

In our laboratory, we conduct interdisciplinary research to study gene expression regulation in human cells, during normal development, and in disease states. Specifically, we employ a variety of computational, genomics, transcriptomic, and proteomics based approaches to study the cross-talk between transcriptional and post-transcriptional regulation and its role in dictating pluripotency and cell fate decisions in human embryonic stem cells. In addition, we develop computational models and novel single-cell genomics technologies for predicting the effect of viral infections on the host cells and study changes in gene expression in placenta and embryo cells subjected to viral infections during pregnancy.

Awards:

2016                Cell Circuit Research Award- Klaman cell observatory

2010                Taub Prize for excellence in science

Recent Publications:
  • Paz I, Kosti I, Ares M. Jr., Cline M and Mandel-Gutfreund Y.RBPmap: a web server for mapping binding sites of RNA-binding proteins. Nucleic Acids Res. W361-7 (2014). DOIi: 10.1093/nar/gku406      PMID: 24829458
  • Enav H, Mandel-Gutfreund Y, Béjà O.  Comparative metagenomic analyses reveal viral-induced shifts of host metabolism towards nucleotide biosynthesis. Microbiome. 2:9 (2014).DOIi: 10.1186/2049-2618-2-9            PMID: 24666644
  • Singer M, Kosti, I,Pachter L., Mandel-Gutfreund Y.  A diverse epigenetic landscape at human exons with implication for expression. Nucleic Acids Res 43:3498-508 (2015).DOIi: 10.1093/nar/gkv153                  PMID: 25765649
  • Dror I, Golan T, Levy C, Rohs R and Mandel-Gutfreund Y. A widespread role of the motif environment on transcription factor binding across diverse protein families. Genome Research25:1268-80 (2015). DOI: 10.1101/gr.184671.114 PMID: 26160164
  • Polishchuk M, Paz I, Yakhini Z, Mandel-Gutfreund Y. SMARTIV: combined sequence and structure de-novo motif discovery for in-vivo RNA binding data. Nucleic Acids Res. 46:W221-W228 (2018). DOI: 10.1093/nar/gky453       PMID: 29800452
  • Budowski-Tal I, Kolodny R, Mandel-Gutfreund Y. A Novel Geometry-Based Approach to Infer Protein Interface Similarity. Sci Rep. 8: 8192 (2018) DOI: 10.1038/s41598-018-26497-z    PMID: 29844500
  • Enav H, Kirzner S, Lindell D, Mandel-Gutfreund Y, Béjà O.Adaptation to sub-optimal hosts is a driver of viral diversification in the ocean. Nat Communion. 8:4698 (2018).DOI: 10.1038/s41467-018-07164-3   PMID: 30409965
  • Yelin I, Aharony N, Tamar ES, Argoetti A, Messer E, Berenbaum D, Shafran E, Kuzli A, Gandali N, Shkedi O, Hashimshony T, Mandel-Gutfreund Y, Halberthal M, Geffen Y, Szwarcwort-Cohen M, Kishony R. Evaluation of COVID-19 RT-qPCR Test in Multi sample Pools. Clin Infect Dis. 71(16):2073-2078. (2020)
    DOI: 10.1093/cid/ciaa531.     PMID:  32358960
  • Dvir S, Argoetti A, Lesnik C, Roytblat M, Shriki K, Amit M, Hashimshony T, Mandel-Gutfreund Y. Uncovering the RNA-binding protein landscape in the pluripotency network of human embryonic stem cells. Cell Rep. 35(9):109198. (2021)
    DOI: 10.1016/j.celrep.2021.109198.      PMID: 34077720.
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Open Positions:

The laboratory of Prof. Yael Mandel-Gutfreund (Prof. of Biology and Computer Sciences) at the faculty of Biology at the Technion studies gene expression regulation in human cells in healthy and disease states, combining computational and experimental approaches.

The lab is seeking for

  • Graduate students (master / Ph.D.) and Postdoctoral fellows with computational knowledge and experience, for projects involving big data analysis and deep learning.
  • Graduate students (master / Ph.D.) with a degree in biology/biotechnology/biomedicine for experimental projects. Preference for students with lab experience.
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