Tackling biological context, one network at a time: Examples from network biology and network pharmacology

Dr. Arda Halu

Harvard Medical School, Brigham and Women’s Hospital



Networks have proven time and again to be highly versatile tools in modeling biological interactions, finding useful applications in basic and clinical research alike. In the majority of these applications, however, the inherently context-specific nature of these interactions remains largely unaccounted for, despite increasingly granular and multi-dimensional biomedical data. In this seminar, I will present two network-based methods that we have recently developed to address, in a context-aware manner, present challenges related to computational drug discovery and cellular signaling. I will first talk about our method that uses a large-scale pharmacogenomic database to build over 50 cell type-specific gene-perturbation networks and integrates these networks with diverse disease phenotypes and cheminformatic data for a nested prioritization of cell lines and perturbations. I will demonstrate that our method outperforms currently available techniques in terms of predictive power and offers the potential to be a feasible blueprint for a cell type-specific drug discovery and repositioning platform. I will then switch over to a recently published multilayer network-based statistical framework from our lab that uses high-dimensional edges, or multilinks, to model crosstalk between signaling pathways. I will show that using statistically overrepresented multilinks as proxies of crosstalk results in better identification of signaling crosstalk compared to single layer-based methods, suggesting the utility of the multilayer modeling of signaling crosstalk, with potential future applications to extend our approach to tissue- and disease-specific crosstalk.

Date: May 22, 2024 (Wed.) 22:00 – 23:00
Place: Zoom
Host: Shinya Kuroda

If you would like to attend, please email us at info.kuroda-lab [at] bs.s.u-tokyo.ac.jp and we will send you the Zoom URL. Please use your institution’s e-mail address and let us know your name and affiliation.