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: tdm-itiv-abx (new) 2021/07/21
meet.google.com/xsv-unow-vbg (expired)
If you face any problem to login please text us to our WhatsApp : +91-8648813686 on the meeting date within 17:00 Hour.
# 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 Retired 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.
