Jennifer Wilson, PhD

Jennifer Wilson, PhD

Assistant Professor, Department of Bioengineering

Languages

English

Education

Fellowships

Bioengineering, Stanford University, Stanford, CA, 2018
Chemical and Systems Biology, Stanford University, Stanford, CA, 2021

Internship

Center of Excellence in Regulatory Science and Innovation (CERSI) Intern, Genentech, South San Francisco, CA, 2019

Degrees

PhD, Massachusetts Institute of Technology, Cambridge, MA, 2016
BS, University of Virginia, Charlottesville, VA, 2010

Scientific Interests

Protein-protein interaction networks connect drug targets to downstream proteins to understand cascading cellular effects. However, downstream proteins are not routinely used during drug-target identification. Downstream and pathways effects are important for understanding multiple disease areas, especially dysregulated pathways in cancer. One of the goals of her research is to develop network models of drug downstream effects with the aim of using these models to predictively identify novel drug targets. As a graduate student, Dr. Wilson used protein-protein interaction networks to identify new pathways in leukemia and growth-factor-driven cancers. In unpublished work from her postdoc, she developed a novel network synergy metric for prioritizing new druggable targets based on downstream associations to known disease pathways.

Highlighted Publications

Wilson JL, Lu D, Corr N, Fullerton A, Lu J. An in vitro quantitative systems pharmacology approach for deconvolving mechanisms of drug-induced, multilineage cytopenias. PLos Comp Bio. 2020 Jul 231; 16(7): e1007620. PubMed PMID: 32701980, PMCID: PMC7402526.

Wilson JL, Racz R, Liu T, Adeniyi O, Sun J, Ramamoorthy A, Pacanowski M, Altman RB. PathFX provides mechanistic insights into drug efficacy and safety for regulatory review and therapeutic development. PLos Comp Bio. 2018 Dec 7; 14(12):e1006614. PubMed PMID: 30532240. PubMed Central PMCID: PMC6285459.

Wilson JL, Kefaloyianni E, Stopfer L, Harrison C, Sabbisetti VS, Fraenkel E, Lauffenburger DA, Herrlich A. Functional Genomics Approach Identifies Novel Signaling Regulators of TGFα Ectodomain Shedding. Mol Cancer Res. 2018 Jan;16(1):147-161. PubMed PMID: 29018056; PubMed Central PMCID: PMC5859574.

Wilson JL, Dalin S, Gosline S, Hemann M, Fraenkel E, Lauffenburger DA. Pathwaybased network modeling finds hidden genes in shRNA screen for regulators of acute lymphoblastic leukemia. Integr Biol (Camb). 2016 Jul 11;8(7):761-74. PubMed PMID: 27315426; PubMed Central PMCID: PMC5224708.