Systems Biology Center New York is a trans-disciplinary center that uses systems approaches to study pathophysiological processes and drug action. We are a highly collaborative group of researchers both basic &clinical, and educators from several universities in the New York area. Center investigators have expertise in genomics, biochemistry and molecular biology, proteomics, in cell biology and visualization of signaling reactions live cells, in tissue/organ physiology &pathophysiology, clinical imaging and in pharmacology. At the computational level we have expertise in statistical models, graph-theory network based analyses, mathematical biology and dynamical modeling including ODE, PDE and stochastic models. Melding the expertise of various disciplines we work at various scales of biological organization to make substantive contributions to the emerging fields of systems pharmacology and precision medicine. During the next term of this grant, we will use our complementary expertise in a highly integrated manner to develop and disseminate approaches that provide a mechanistic understanding of how molecular interactions within regulatory networks result in tissue and organ behavior and how this information can be used to predict new drug targets, repurpose existing drugs and predict adverse events in the context of genomic and epigenomic characteristics. Our research activities are focused on four thematic projects that will integrate network analysis and enhanced pharmacodynamic modeling to study different facets of drug action in three diseases: glioblastomas, depression and heart failure and an adverse event-peripheral neuropathy. Our research activities are seamlessly connected to our education and outreach activities that include working with the faculty at Colgate to enhance the Systems Biology Minor program for undergraduates. We plan to offer three free online Systems Biology courses and develop quantitative biology courses for community colleges. We will develop new interactions with Systems Biology Programs in Brazil and Ireland and continue and grow our highly successful undergraduate summer program for CUNY students from diverse backgrounds to prime the pipeline for the next generation of quantitative biomedical scientists.
This project will contribute to our understanding of how the action of drugs both therapeutic and adverse is related to genomic and epigenomic changes. This understanding will allow us to develop classifiers and predictors of drug efficacy and adverse event occurrence in individual patients and thus contribute to the development of precision and personalized medicine.
|Lee, Young-Seon; Hwang, Minki; Song, Jun-Seop et al. (2016) The Contribution of Ionic Currents to Rate-Dependent Action Potential Duration and Pattern of Reentry in a Mathematical Model of Human Atrial Fibrillation. PLoS One 11:e0150779|
|Leffler, Shoshana R; LeguÃ©, Emilie; AristizÃ¡bal, Orlando et al. (2016) A Mathematical Model of Granule Cell Generation During Mouse Cerebellum Development. Bull Math Biol 78:859-78|
|Stern, Alan D; Rahman, Adeeb H; Birtwistle, Marc R (2016) Cell size assays for mass cytometry. Cytometry A :|
|Smith, Gregory R; Birtwistle, Marc R (2016) A Mechanistic Beta-Binomial Probability Model for mRNA Sequencing Data. PLoS One 11:e0157828|
|Byrne, Kate M; Monsefi, Naser; Dawson, John C et al. (2016) Bistability in the Rac1, PAK, and RhoA Signaling Network Drives Actin Cytoskeleton Dynamics and Cell Motility Switches. Cell Syst 2:38-48|
|Gallo, James M; Birtwistle, Marc R (2015) Network pharmacodynamic models for customized cancer therapy. Wiley Interdiscip Rev Syst Biol Med 7:243-51|
|Klinke 2nd, David J; Birtwistle, Marc R (2015) In silico model-based inference: an emerging approach for inverse problems in engineering better medicines. Curr Opin Chem Eng 10:14-24|
|Bastiaens, Philippe; Birtwistle, Marc R; BlÃ¼thgen, Nils et al. (2015) Silence on the relevant literature and errors in implementation. Nat Biotechnol 33:336-9|
|Azeloglu, Evren U; Iyengar, Ravi (2015) Good practices for building dynamical models in systems biology. Sci Signal 8:fs8|
|Birtwistle, Marc R (2015) Analytical reduction of combinatorial complexity arising from multiple protein modification sites. J R Soc Interface 12:|
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