Society for Systems Biology & Translational Research (SSBTR) is a registered (and also both 12A & 80G certified) not-for-profit scientific society organizes an International Webinar Series Lectures on Translational Systems Biology.
All are cordially invited. For date, time and link and other details are as below:
GOOGLE MEET Link: url (https://meet.google.com/qjb-utgp-ymk)
# Speaker: Dr. María Rodríguez Martínez at IST 17:00 Hour
Title : Understanding the Determinants to T-cell Receptor Binding in Cancer Immunotherapies.
Abstract : The activity of the adaptive immune system depends on the recognition of foreign antigens by T cells by their specific T cell receptors (TCRs). A correct understanding of the determinants that govern the binding of T cells to cancer neo-antigens is crucial to design better immunotherapies, distinguished by more effective binding profiles and less cross-reactive effects. Our group has recently developed TITAN, a multi-modal deep learning model that predicts the binding affinity between TCRs and epitopes, outperforming the state of the art in this difficult task. Interestingly, TITAN allows to study independently the generalization capabilities to new TCRs and/or epitopes, which previous models have struggled with. Furthermore, to enhance the interpretability of the predictions, TITAN exploits interpretable attention mechanisms that selectively highlight the patterns in the TCR and epitope sequence that are more important to make the prediction. In parallel, we are investigating the use of alternative techniques to enhance prediction transparency, for instance, based on the use of probabilistic graphical models. This is an example of how the combined used of AI and traditional mathematical approaches can result in more performant models able to make great strides into a multitude of fields, including prediction of autoantigens in autoimmune diseases, development of immunotherapies for cancer, or vaccine design.
Bio-sketch : Dr. María Rodríguez Martínez is the Technical Lead of the group of Systems Biology at IBM Research – Zürich, and an associated member of the Department of Biology at ETH. She did her undergraduate studies in Physical Sciences at Universidad Complutense de Madrid and PhD in Theoretical Cosmology, at the Institut d’Astrophysique de Paris. Her PhD research focused on developing cosmological models of the early evolution of the universe. After completing her PhD, she moved to the Hebrew University in Jerusalem to focus on astrophysical bounds. In 2007, she transitioned into the field of Systems Biology at the Weizmann Institute of Science in Rehovot (Israel). In 2009, she moved to Columbia University where she developed quantitative models to understand cancer gene dysregulation. Her current research focuses on the development of computational and statistical approaches to unravel cancer molecular mechanisms using high- throughput multi-omics datasets and single-cell molecular data. In recent years her team has focused on the development of artificial intelligence approaches for cancer personalized medicine and drug modelling. Supporting these efforts, she is currently the technical leader of a large H2020 consortium, iPC, focused on developing personalized medicine approaches for pediatric cancers. More recently, her team is working in the development of multi-scale hybrid models of the immune system, combining both AI and mechanistic approaches, to enable the in silico optimization of immunotherapies.
# Speaker : Prof. Dhananjay Bhattacharyya at IST 18:00 Hour
Title : RNA Three-dimensional Structure and Non-canonical Base Pairing
Abstract : It is well known now that mRNA is not the only form of RNA and RNA performs various gene regulatory and other functions in the cellular environment. These specific functions demand stable three-dimensional structures of various RNA, such as tRNA, ribosome, riboswitch, miRNA, etc. The only secondary structural element of RNA, like 𝞪-helix, 𝞫-sheet, etc. of proteins, is double helix. Traditionally we conceptualize double helix as that proposed by Watson and Crick in 1953 stabilized by specific pairing through hydrogen bonds between A and T (or U in RNA) and those between G and C. Such double helices of DNA are extremely stable and expose different sites of the bases for specific molecular recognition by gene regulatory proteins. In RNA however, these are not possible and nature utilized few types of base pairs completely different from those proposed by Watson and Crick. These non-canonical base pairs have been shown to be specific, stable, capable to form double helix and provide sufficient sites for proper molecular recognition. In this lecture I would be focusing on such non-canonical base pairs from various aspects.
Bio-sketch : Prof. Dhananjay Bhattacharyya is a Professor of Biophysics at Saha Institute of Nuclear Physics (SINP), associate member of Interdisciplinary Center for Mathematics and Computation, SINP and Advanced Material Research of S.N. Bose National Center for Basic Sciences. He graduated in Physics from University of Calcutta and received his Ph.D. from Indian Institute of Science, Bangalore and got post-doctoral experience from National Institutes of Health, Maryland, USA. His research interest includes Quantum Chemistry, Molecular Dynamics, Structure-Function correlation of biological macromolecules and development of tools for bioinformatics applications. He has published more than 60 research articles, trained more than 12 doctoral students and developed several bioinformatics softwares namely, NUPARM, BPFIND, PyrHBFIND,RNAHelix etc. He developed techniques in understanding the effects of base sequence on DNA double helices and its interactions with other molecules. It was necessary to analyze 3D structures of different functional RNA molecules after ribosome and several other RNA were solved by x-ray crystallography. Such analysis in terms of different quantitative parameters, such as relative orientation between bases of base pair or between successive base pairs in double helical regions or identification of different types of base pairs in a large complex RNA structure, require specially designed software and were unavailable in such a nascent field. His team developed several software for such analysis and application of those identified several important non-canonical base pairs apart from the Watson-Crick type A:U and G:C. His team used different simulation techniques with classical as well as quantum mechanical methods to understand their properties in terms of strength, stability, dynamics, planarity, etc.