Centre for Modeling & Simulation
Savitribai Phule Pune University

Colloquium | Data-driven modeling using complex networks to understand human disease biology


Title Data-driven modeling using complex networks to understand human disease biology
Speaker Abhijeet Sonawane, Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, USA

Dr. Abhijeet Sonawane completed his PhD at the Centre for Modeling and Simulation, SPPU. He is now a postdoctoral researcher at the Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School Boston, USA. His research interests include complex systems, network theory, nonlinear dynamics, social network analysis and, more recently, systems and computaional biology and biostatistics involving big data.
Date & Time Monday, 19 November 2018 | 10:00-11:30
Venue Kelkar Lab, CMS, SPPU
Abstract In this talk, we will try to understand complex networks phenomenology and its applications in various fields including epidemic spreading, extreme events statistics, and human disease biology. I will cover the basics of network theory, establish parallels with machine learning, and underline the commonalities while delineating their specialties. The primary aim of this talk to is to introduce data-driven modeling using networks and understand the strength and weaknesses of the network paradigm. I will also talk about the problem of gene regulation and how multiple OMICS data can be integrated to obtain biologically meaningful models to understand various phenotypes including disease. I will also walk the audience through my journey in understanding tissue-specific gene regulation using regulatory networks. The level of the talk will be undergraduate and the talk will be very interdisciplinary. The aim of the talk is to inspire students to look beyond the methods, models, and terminologies but rather focus on holistic questions one can attempt to understand using big data.
Organizer/Host pranav.kulkarni@cms.unipune.ac.in




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