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Mohammed AlQuraishi, Ph.D.

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Biography
Stanford UniversityPh.D.06/2012Genetics
Stanford UniversityM.S.06/2010Statistics

Overview
Mohammed AlQuraishi is a Fellow in Therapeutic Science at Harvard Medical School, where he works at the intersection of machine learning, statistical mechanics, and biophysics. His research focuses on developing computational models of biomolecules and their interactions. He has used these models to study signaling pathways in humans, and to understand how genetic mutations rewire the circuitry of cancer cells. More recently, he developed the first end-to-end differentiable model for learning protein structure directly from data. Prior to the start of his academic career, Mohammed spent three years founding three startups in the mobile computing space. He holds an M.S. in Statistics and a Ph.D. in Genetics from Stanford University.

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Bibliographic
Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
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PMC Citations indicate the number of times the publication was cited by articles in PubMed Central, and the Altmetric score represents citations in news articles and social media. (Note that publications are often cited in additional ways that are not shown here.) Fields are based on how the National Library of Medicine (NLM) classifies the publication's journal and might not represent the specific topic of the publication. Translation tags are based on the publication type and the MeSH terms NLM assigns to the publication. Some publications (especially newer ones and publications not in PubMed) might not yet be assigned Field or Translation tags.) Click a Field or Translation tag to filter the publications.
  1. Cunningham JM, Koytiger G, Sorger PK, AlQuraishi M. Biophysical prediction of protein-peptide interactions and signaling networks using machine learning. Nat Methods. 2020 Jan 06. PMID: 31907444.
    Citations:    
  2. Iddo Drori, Darshan Thaker, Arjun Srivatsa, Daniel Jeong, Yueqi Wang, Linyong Nan, Fan Wu, Dimitri Leggas, Jinhao Lei, Weiyi Lu, Weilong Fu, Yuan Gao, Sashank Karri, Anand Kannan, Antonio Moretti, Mohammed AlQuraishi, Chen Keasar, Itsik Pe'er. Accurate Protein Structure Prediction by Embeddings and Deep Learning Representations. arXiv. 2019; (1911.05531). View Publication.
  3. AlQuraishi M. AlphaFold at CASP13. Bioinformatics. 2019 Nov 01; 35(22):4862-4865. PMID: 31116374.
    Citations:    
  4. Alley EC, Khimulya G, Biswas S, AlQuraishi M, Church GM. Unified rational protein engineering with sequence-based deep representation learning. Nat Methods. 2019 Dec; 16(12):1315-1322. PMID: 31636460.
    Citations:    
  5. AlQuraishi M. ProteinNet: a standardized data set for machine learning of protein structure. BMC Bioinformatics. 2019 Jun 11; 20(1):311. PMID: 31185886.
    Citations:    
  6. AlQuraishi M. End-to-End Differentiable Learning of Protein Structure. Cell Syst. 2019 Apr 24; 8(4):292-301.e3. PMID: 31005579.
    Citations:    
  7. Alley E., Khimulya G., Biswas S., AlQuraishi M., Church G. Unified rational protein engineering with sequence-only deep representation learning. bioRxiv. 2019; 1101(10):589333. View Publication.
  8. AlQuraishi M. Parallelized Natural Extension Reference Frame: Parallelized Conversion from Internal to Cartesian Coordinates. J Comput Chem. 2019 Mar 15; 40(7):885-892. PMID: 30614534.
    Citations:    Fields:    
  9. AlQuraishi M, Sorger PK. Reproducibility will only come with data liberation. Sci Transl Med. 2016 05 18; 8(339):339ed7. PMID: 27194726.
    Citations: 1     Fields:    Translation:Humans
  10. AlQuraishi M, Tang S, Xia X. An affinity-structure database of helix-turn-helix: DNA complexes with a universal coordinate system. BMC Bioinformatics. 2015 Nov 19; 16:390. PMID: 26586237.
    Citations:    Fields:    
  11. AlQuraishi M, Koytiger G, Jenney A, MacBeath G, Sorger PK. A multiscale statistical mechanical framework integrates biophysical and genomic data to assemble cancer networks. Nat Genet. 2014 Dec; 46(12):1363-1371. PMID: 25362484.
    Citations: 16     Fields:    Translation:HumansCells
  12. AlQuraishi M, McAdams HH. Three enhancements to the inference of statistical protein-DNA potentials. Proteins. 2013 Mar; 81(3):426-42. PMID: 23042633.
    Citations: 2     Fields:    Translation:Cells
  13. AlQuraishi M, McAdams HH. Direct inference of protein-DNA interactions using compressed sensing methods. Proc Natl Acad Sci U S A. 2011 Sep 06; 108(36):14819-24. PMID: 21825146.
    Citations: 10     Fields:    Translation:Cells
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Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.