Friday, 4 June 2021

SSBTR International Webinar Lecture Series : Day 2021 June 26 (Saturday) at IST 15:45 Hour

 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: 

# Speaker : Professor Ernst Titovets IST : 16:00 Hour 

Title : Novel Nanofluidic Mechanism and Computational Model of the Brain Water Metabolism
Abstract :
Brain water metabolism ensures the processes of cellular communication, transit of the signaling molecules, neurotransmitters, cytokines and substrates, participates in the clearance of pathogenic metabolites. Many neurological conditions that present serious clinical problems arise from altered fluid flow (e.g. Alzheimer’s disease, idiopathic normal pressure hydrocephalus, migraine, traumatic brain injury and stroke). At present, the orthodox theory fails to explain the accumulated experimental evidence and clinical data on the brain water metabolism. Modeling becomes an important approach to testing current theories and developing new working mechanisms. 

A novel computational model of brain water metabolism has been developed and explored. Using an interdisciplinary approach the long-recognized nano-dimentionality of the brain interstitial space is viewed as a nano-fluidic domain with the fluid flow there governed by the slip-flow principles of nano-fluidics. Aquaporin-4 (AQP4) of the astrocyte endfeet membranes ensures kinetic control over water movement across the blood-brain barrier. The pulsatory intracranial pressure presents the driving force behind the transcapillary water flow. The model demonstrates good predictability in respect to some physiological features of brain water metabolism and relevance in explaining clinical conditions. The model may find its use in neuro-biological research, development of the AQP4-targeted drug therapy, optimization of the intrathecal drug delivery to the brain tumours, in a research on a broad spectrum of water-metabolic-disorder-related conditions.

Bio-sketch :
Professor Ernst Titovets, M.D., Ph.D. holds a position of Professor at the Department of Neurosurgery, Republican Research and Clinical Center of Neurology and Neurosurgery, Minsk, Belarus. He is a researcher, author, translator and interpreter was born in Krasnoyarsk, Siberia. He graduated from the Minsk State Medical Institute and undertook post-graduate research in biochemistry. He earned his Ph. D. degree from the Academy of Sciences of Belarus for his research on endergonic transport of Ca++ by the mitochondria. His Doctor of Sciences Degree in biology he obtained from the St. Petersburg State University, Russia for his pioneering research on the biochemical action mechanism of new amino derivatives of orthobenzoquinone. Appointed to a number of scientific research councils, he has authored or co-authored four research books, 14 patents and over 400 research papers and as an interpreter, he translated three books. As an Author, he wrote a book Oswald: Russian Episode that has appeared in three editions. The book presents an in deep historic investigation of life of Lee Harvey Oswald, an alleged assassin of the President John Kennedy. Currently he is concentrated on a research on brain water metabolism and related issues conducted from the nanofluidic approach. He is a principal researcher, at the Republican Research and Clinical Centre of Neurology and Neurosurgery in Minsk, Belarus where he heads a scientific research group. 


# Speaker : Professor Dimitrios A. Karras IST : 17:00 Hour  

Title : An Overview of MRI-based Brain Tumors Diagnosis Using Artificial Intelligence and Machine Learning Methods
Abstract :
Brain tumor segmentation and diagnosis is an important task in medical image processing. Early diagnosis of brain tumors plays an important role in improving treatment possibilities and increases the survival rate of the patients. Manual segmentation of the brain tumors for cancer diagnosis, from large amount of MRI images generated in clinical routine, is a difficult and time consuming task. There is a need for automatic brain tumor image segmentation. The purpose of this lecture is to provide a state of the art review of MRI-based brain tumor segmentation and diagnosis methods and recent trends in the use of Artificial Intelligence and Machine Learning methodologies to efficiently tackle the problem. the State-of-the-art results and open problems will be reviewed. Although there are several existing review papers, focusing on traditional methods for MRI-based brain tumor image segmentation, this lecture will focus on outlining the recent trends in this field attempting an assessment of the current state as well as of the developments to standardize MRI-based brain tumor segmentation and diagnosis methods into daily clinical routine.
Bio-sketch : Professor Dimitrios A. Karras received his Diploma and M.Sc. Degree in Electrical and Electronic Engineering from the National Technical University of Athens (NTUA), Greece in 1985 and the Ph. Degree in Electrical Engineering, from the NTUA, Greece in 1995, with honors. From 1990 and up to 2004 he collaborated as visiting professor and researcher with several universities and research institutes in Greece. Since 2004, after his election, he has been with the Sterea Hellas Institute of Technology, Automation Dept., Greece as associate professor in Digital Systems and Signal Processing, till 12/2018, as well as with the Hellenic Open University, Dept. Informatics as a visiting professor in Communication Systems (the latter since 2002 and up to 2010). Since 1/2019 is Associate Prof. in Digital Systems and Intelligent Systems, Signal Processing , in National & Kapodistrian University of Athens, Greece, School of Science, Dept. General as well as adjunct Assoc. Prof. Dr. with the EPOKA and CIT universities, Computer Engineering Dept., Tirana. He has published more than 70 research refereed journal papers in various areas of intelligent and distributed/multiagent systems, pattern recognition, image/signal processing and neural networks as well as in bioinformatics and more than 185 research papers in International refereed scientific Conferences. His research interests span the fields of intelligent and distributed systems, multiagent systems, pattern recognition and computational intelligence, image and signal processing and systems, biomedical systems, communications and networking as well as security. He has served as program committee member as well as program chair and general chair in several international workshops and conferences in the fields of signal, image, communication and automation systems. He is, also, former editor in chief (2008-2016) of the International Journal in Signal and Imaging Systems Engineering (IJSISE), academic editor in the TWSJ, ISRN Communications and the Applied Mathematics Hindawi journals as well as associate editor in various scientific journals, including CAAI, IET. He has been cited in more than 2321 research papers, his H/G-indices are 20/48 and his Erdos number is 5. His RG score is 31.42.

Saturday, 1 May 2021

CANCELLED : SSBTR International Webinar Lecture Series Day: 2021 May 26 IST 16:45 Hour --> & Re-scheduled on 2021 July 21 (Wed) IST 16:45 Hour

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.


The same event is re-scheduled on July 21 (Wednesday) 2021 at IST 16:45 Hour

All are cordially invited. For date, time and link and other details are as below:

Re-scheduled Flyer


GOOGLE MEET Link: url (

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.

Thursday, 1 April 2021

SSBTR International Webinar Lecture Series Day: 2021 April 11 IST 15:45 Hour

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 as below:

GOOGLE MEET Link: url (

# Speaker: Dr. Dibyendu K Ray at IST 16:00 Hour

Title : Advances in Neurosurgery- Glimpses of the Role of Technology in the Operating Room
Abstract :
There has been rapid advancements in the use of technology in the operating room by neurosurgeons all over the world. The nature of the biology of the central nervous system in humans is such that being permanent cells, the neurons do not regenerate. Neurosurgeons have been aware of the critical nature and biology of the tissues they deal with and have therefore been at the forefront in adapting new technology to benefit their patients. The technological revolution in neurosurgery has been fueled as much by the developments in computer technology and connectivity as by the advancements in material science and precision engineering. The seminar deals with the use of certain available equipment to demonstrate how clinicians and surgeons have adapted technology to positively impact and improve the lives of their patients.

Bio-sketch : Dr. Dibyendu K Ray M.S., M.Ch. (Neurosurgery) is a Senior Neurosurgeon Consultant at AMRI Hospital. Prior to starting his neurosurgical practice, he was working as an Assistant Professor of Neurosurgery at the Bangur Institute of Neurosciences, Kolkata, the apex institute for neurosurgical training in the state. After receiving his basic medical training from R G Kar Medical College Kolkata, Dr. Ray completed his post graduation in surgery from University of Rajasthan and then went on to achieve his postdoctoral degree in neurosurgery from the PGIMER, Chandigarh. Thereafter he trained in the USA at the University of Virginia, the Oregon Health Science University, and the University of Illinois College of Medicine at Peoria. Subsequently he qualified for the Diploma of the European Society of the Minimally Invasive Neurologic Therapy and the Fellowship of the Royal College of Surgeons of England. Despite his busy clinical schedule, he has published several articles in peer reviewed journals and has several book chapters to his credit. He is serving as the Honorary President of the Society for Systems Biology & Translational Research (SSBTR). 


Monday, 1 March 2021

SSBTR International Webinar Lecture Series Day: 2021 March 14 (Sunday) IST 13:45 Hour

 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 as below:

GOOGLE MEET Link: url (

Day: 2021-March-14 (Sunday)    Time: IST 14:00 Hour

# Speaker: Dr. Milana Frenkel-Morgenstern
Title: Diagnosis of Glioma Tumors Using Circulating Cell-Free DNA

Abstract: Gliomas are the most frequent brain tumors, making up about 30% of all brain and central nervous system tumors, and 80% of all malignant brain tumors. Diagnosis of different glioma tumor types and their tumor grade is an essential step to suggest a right treatment for the glioma patients. Existing standard diagnostic technique for glioma tumor includes tissue biopsy, which is a highly invasive and hence a risky technique for the patient’s survival. ‘Liquid biopsy’ is a new and recently developed non-invasive cancer diagnostic technique. This technique includes collection of blood or urine samples and diagnosis of cancer based on analyzing molecular bits or cancer cells that are released from tumor tissue into the blood or urine system. Circulating cell-free DNA (cfDNA) fragments is one those molecular bits that are released into the bloodstream after rapid apoptosis or necrosis of the tumor cells in the cancer patients. Our goal is to do comprehensive study between distinct types of glioma cancer tumors and cfDNA of the respective patients, to elucidate the scope of cfDNA in liquid biopsy technique for glioma diagnosis. We have successfully detected glioma specific mutations such as IDH1, IDH2, PDGFRA, NOTCH1, PIK3R1 and TP53, from cfDNA isolated from the plasma of glioma patients and could relate these mutations to the different tumor grades of glioma. Moreover, we have identified unique gene-gene fusions that provide a personalized drug response to glioma treatment. Our study may help in developing liquid biopsy technique for glioma tumor diagnosis and in its prognosis for monitoring the glioma treatment by non-invasive approach, and will eventually help physicians to decide on the right treatment while bypassing the existing ''wait-and-see' approach of treatment monitoring.
Biosketch: Dr. Milana Frenkel-Morgenstern, Senior Lecturer and Head of Cancer Genomics and Bio-computing of Complex Diseases, Azrieli Faculty of Medicine,
Bar-Ilan University. She has completed her Ph.D in the Weizmann Institute of Science, Israel in 2006. She made her first postdoc in the lab of Prof. Uri Alon in Systems Biology in the Weizmann Institute of Science, Israel, and the second postdoc in the lab of Prof. Alfonso Valencia in the Spanish National Cancer Research Centre (CNIO), Spain. She has published more than 50 papers in reputed journals and serving as an editorial board member of repute. She is a founder of special scientific Art in Science competition at the international Bioinformatics conferences since 2008, a chair of the ISCB affiliated Israeli Bioinformatics group. Her group has developed unique protocols for the cell free DNA isolation and its analysis using unique and patented techniques, the group in working in evolution of protein interaction networks.  

# Speaker: Dr. Durjoy Majumder 
Title: Development of Algorithm for Automated Diagnosis of Leukemia : A Systems Biology Application for Preventive Oncology
Abstract: Bone marrow biopsy has become an integral part of leukemia diagnosis and its treatment. Several advancements are being made towards the analysis of digital images of biopsy samples. Recently FDA approved the procedures of digital health. In tune with that digital image analysis has become propelled. With the advent of high-throughput technologies, scientific community becomes interested to look into the red blood cells (RBCs) for early detection of cancer, including leukemia. The reasons are due to their abundance in peripheral blood and hence, easily accessible compared to bone marrow biopsy procedure. High magnification and high-resolution electron microscopy based ultra-structural analysis of RBCs already proved the utility of the hypothesis about a decade ago. However, in clinical set-up, electron microscopy based procedures are the major bottleneck in implementation of early detection of leukemia. Algorithm based computer vision may be suitable to overcome this limitation. To fill the existing gap a user-friendly MatLab coding is developed for automated analysis of RBC images. RBC images from both normal and leukemia were analyzed with the developed code. Each RBC cells were analyzed individually for each samples of normal and leukemia. So in the output cellular characteristics namely, radius, perimeter, area, convexity, solidity were represented in a quantitative manner. Comparison of mean values between normal and leukemia groups for corresponding variables showed statistical significance (p<0.05). Thus, the developed code successfully distinguishes between RBC cells of leukemia and normal. We hope that this RBC based developed code would be useful in identifying early stage of leukemia in an individual patient; however, for this ~100 RBC cells are needed to be analyzed. Thus it is expected that the developed code may play a role in preventive oncology.
Biosketch: Dr. Durjoy Majumder, Assistant Professor of Physiology, West Bengal State University, received his Ph.D. in 2006 from Biophysics & Structural Genomics Division of Saha institute of Nuclear Physics. He gained a multi-/interdisciplinary research experience by working in science, medical and engineering faculties. He worked in different tertiary grade medical institutions like School of Tropical Medicine, Kolkata and Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow. Before joining to present position he hold a faculty position in engineering faculty of Institute Indian Institute Engineering Science & Technology, Shibpur. His research interests include cancer, cancer immunology, cancer systems biology, systems pharmacology, pre- and post-clinical phases of cancer management. He has more than 50 research publications in different peer-reviewed journals, conferences, book chapters and book. He holds positions of editorial board members in different international journals. In the area of systems biology, his research group has developed a new philosophical outlook called “Middle-out Rationalistic Analysis” for cancer systems.

Event Photos: 




Durjoy Majumder, Ph.D.

Sunday, 24 January 2021

SSBTR International Webinar Lecture Series Day: 2021 February 27 (Saturday) IST 16:45 Hour

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 as below:

GOOGLE MEET Link: url (

Day: 2021-Feb-27 (Saturday)  Time: IST 17:00 Hour

# Speaker: Prof. Jan-Hendrik (Jannie) Hofmeyr
Title: The Metabolic Marketplace: How the cellular economy of supply and demand is regulated
Abstract: A central tenet of systems biology is that organisms, cells, genes and proteins are complex structures whose relationships and properties are largely determined by their functional organisation. In terms of functional organisation cellular metabolism can be regarded as a chain of coupled factories: a catabolic factory transforms nutrients into carbon skeletons and captures chemical energy and reducing power. These catabolic products serve as input to an anabolic factory that synthesizes the building blocks for macromolecular syntheses (amino acids, nucleotides, simple lipids, etc.). The factories for protein, polynucleotide, complex carbohydrate and lipid synthesis form the end of the chain and lead to growth. I show how this view of the functional organisation of the cell underlies a quantitative formalism and a general theory for understanding the cell as an integrated molecular economy of coupled supply and demand systems that have evolved regulatory mechanisms that enable them to fulfil specific functions such as control of flux or homeostatic maintenance of metabolite concentrations.
Jan-Hendrik (Jannie) Hofmeyr is Emeritus Professor of Biochemistry and has been a member of the Biochemistry Department at the Stellenbosch University since 1975. He obtained his Ph.D. in 1986 at the University of Stellenbosch. His research of the past 40 years has been in the fields of metabolic control analysis and computational systems biology where his main focus has been the understanding of the regulatory design of metabolism. He also co-directed the Centre for Complex Systems in Transition where an additional research focus was the functional organisation that underlies cellular self-fabrication. He is a Fellow and was President of the Royal Society of South Africa, and is a member of the Academy of Science of South Africa. He is a founder member and served as Vice President of the International Society for Code Biology. 

Event Photo:





Durjoy Majumder, Ph.D. 

Monday, 28 December 2020

SSBTR International Webinar Lecture Series Day: 2021 Jan 12 (Tuesday) and Jan 24 (Sunday)

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. 


All are cordially invited. For date, time and link and other details aas below:

GOOGLE MEET Link: url (

Day: 2021-Jan-12 (Tuesday)     Time: IST 12:45 Hour

# Speaker: Prof. Olivier Gandrillon, Ecole Normale Superieure de Lyon at IST 13:00 Hour
Toward a dynamical network view on a differentiation process
A recent view emerged that stochastic dynamics governing the switching of cells from one differentiation state to another could be characterized by a peak in gene expression variability at the point of fate commitment. We have tested this hypothesis at the single-cell level by analyzing primary chicken erythroid progenitors through their differentiation process and measuring the expression of selected genes at six sequential time-points after induction of differentiation. In contrast to population-based expression data, single-cell gene expression data revealed a high cell-to-cell variability, which was masked by averaging. Shannon entropy was used as as a measure of the cell-to-cell variability in gene expression. Entropy values showed a significant increase, reaching a peak between 8 and 24 h, before decreasing to significantly lower values. We observed that the previous point of maximum entropy precedes an irreversible commitment to differentiation between 24 and 48 h. In conclusion, when analyzed at the single cell level, the differentiation process looks very different from its classical population average view. New observables (like entropy) can be computed, the behavior of which is fully compatible with the idea that differentiation is not a “simple” program that all cells execute identically but results from the dynamical behavior of the underlying molecular network.

Dr. Olivier Gandrillon received PhD degree in biology in 1989. After a two years post-doctoral stay at Caltech, he was appointed a permanent research position at Ecole Normale Supérieure de Lyon in 1989 and started his own team as an independent group leader in 1999 in Université Claude Bernard. He was awarded research director at CNRS in 2009. He moved back to ENS in 2015, where he is now heading a group entitled "Systems Biology of Decision Making". He has a long experience in multidisciplinary projects and interactions between Computer Science, Life Sciences and Mathematics. He is a member of the Dracula Inria team that is devoted to developing mathematical tools for multiscale modeling. He was elected director of the BioSyL research federation since 2011 when the federation was founded. He is the founder of the modeling seminar “Semovi” and of the international conference series “Integrative Post Genomics” (2001-2010) and “LyonSysBio” (since 2014). He was the co-chair of the very successful ICSB2018 conference. He co-authored 72 original publications in a very large range of different disciplinary fields. 

# Speaker: Dr. Bishwajit Das, SSBTR at IST 14:00 Hour
Information Theoretic Multivariate Dependence Analysis of HLA Immune-gene Regulation
Cell surface expression of Human Leukocytic Antigen (HLA) plays a significant role in immune recognition. HLA molecules are classified into two – class I and class II. In different cancers including leukemia, HLA (both class I and II) down-regulation is frequently reported. Regarding its regulation, different transcription factors (TFs) are responsible for its constitutive expression; however, it is also regulated by several inducible TFs. Using 1st order information theory based analysis for HLA and its associated TFs (human) gene expression data reveals that RFXB, an inducible controlling TF plays a major role in both myeloid and lymphoid types of leukemia; however, in lymphoid leukemia CREB1, another inducible TF may play an important role. Application of MaxEnt based multivariate dependence information theory for higher order analysis confirm the same finding along with an indication of the regulatory role of another combination of two TFs namely CIITA and IRF1 for myeloid type leukmic cells. However through this analysis no alteration is noted for HLA class II gene regulation.
Bio-sketch: Dr. Bishwajit Das, is an Investigator of SSBTR. He received his Ph.D. degree in 2021 from West Bengal State University. The field of his research is to understand HLA gene regulation in different non-communicable complex diseases by using different quantitative and analytical methods. He is interested in the development of different analytical tools for immune-informatics. He extensively used Information Theoretic approach in his doctoral thesis. So far eight international research papers are to his credits. He has presented his works in different International conferences and reviewer of leading bioinformatics review journal (Briefings in Bioinformatics).

Event Photos: Day 2021 Jan 12 (Tuesday)

################# COMPLETED ########################

Day: 2021-Jan-24 (Sunday)     Time: IST 17:45 Hour 

# Speaker: Dr. Jianhua Xing, University of Pittsburgh at IST 18:00 Hour 
Title :
Reconstructing cell phenotypic transition dynamics from single cell data
Abstract :
Recent advances in single-cell techniques catalyze an emerging field of studying how cells convert from one phenotype to another, i.e., cell phenotypic transitions (CPTs). Two grand technical challenges, however, impede further development of the field. Fixed cell-based approaches can provide snapshots of high-dimensional expression profiles but have fundamental limits on revealing temporal information, and fluorescence-based live cell imaging approaches provide temporal information but are technically challenging for multiplex long- term imaging. My lab is tackling these grand challenges from two directions, with the ultimate goal of integrating the two directions to reconstruct the spatial-temporal dynamics of CPTs. In one direction, we developed a live-cell imaging platform that tracks cellular status change in a composite multi-dimensional cell feature space that include cell morphological and texture features readily through fluorescent and transmission light imaging. We applied the framework to study human A549 cells undergoing TGF-β induced epithelial-to-mesenchymal transition (EMT). In another direction, we aim at reconstructing single cell dynamics and governing equations from single cell genomics data. We developed a procedure of learning the analytical form of the vector field F(x) and the equation dx/dt = F(x) in the Reproducing Kernel Hilbert Space. Further differential geometry analysis on the vector field reveals rich information on gene regulations and dynamics of various CPT processes.
Bio-sketch :Dr Xing received B.S. in Chemistry from Peking University, M.S. in Chemical Physics from University of Minnesota, and PhD in Theoretical Chemistry from UC Berkeley. After being a postdoc researcher in theoretical biophysics at UC Berkeley and an independent fellow at Lawrence Livermore National Laboratory, he assumed his first faculty position at Virginia Tech, then moved to University of Pittsburgh in 2015. Currently Dr Xing is an Associate Professor in the Computational and Systems Biology Department, School of Medicine, a founding member of Center for Systems Immunology, and an affiliated faculty member of Department of Physics, University of Pittsburgh. He is also an affiliated member of University of Pittsburgh Hillman Cancer Center. Dr Xing’s research uses statistical and chemical physics, dynamical systems theory, mathematical/computational modeling in combination with quantitative measurements to study the dynamics and mechanics of biological processes. Recently his lab focuses on reconstructing information of cell phenotypic transition dynamics from live cell time-lapse images and snapshot high-throughput single cell data. Another related direction is to study how three-dimensional chromosome structure and dynamics, epigenetic modification, and gene regulation are coupled.

# Speaker: Dr. Mohit Kumar Jolly, Indian Institute of Science, Bangalore at IST 19:00 Hour
Title :
Systems biology of cancer metastasis: how do cancer cells coordinate, communicate, and cooperate?

Abstract : Metastasis (the spread of cancer cells from one organ to another) and therapy resistance cause above 90% of all cancer-related deaths. Despite extensive ongoing efforts in cancer genomics, no unique genetic or mutational signature has emerged for metastasis. However, a hallmark that has been observed in metastasis is adaptability or phenotypic plasticity – the ability of a cell to reversibly switch among different phenotypes in response to various internal or external stimuli. Phenotypic plasticity has also been recently implicated in enabling the emergence of resistance for many cancers across multiple therapies. However, a mechanistic understanding of these processes from a dynamical systems perspective remains incomplete. This talk will describe how mechanism-based mathematical models for phenotypic plasticity can enable our improved understanding of cellular decision-making at individual and population levels from these perspectives: a) Multistability (how many cell states exist en route?), b) Reversibility (do cells come across a ‘tipping point’ at specific time and/or dose of inducers beyond which they do not revert?), and c) Cell-cell communication (how do cells affect tendency of their neighbors to exhibit plasticity?). Collectively, our work highlights how an iterative crosstalk between mathematical modeling and experiments can both generate novel insights into the emergent nonlinear dynamics of cellular transitions and uncover previously unknown accelerators of metastasis and therapy resistance. 
Bio-sketch : Dr. Mohit Kumar Jolly received his B.Tech. and M.Tech. degree in Bio-engineering from IIT Kanpur and Ph.D. in Bio-engineering from Rice University He leads the Cancer Systems Biology group at the Centre for BioSystems Science and Engineering, Indian Institute of Science. He has made seminal contributions to decoding the emergent dynamics of epithelial-mesenchymal plasticity (EMP) in cancer metastasis, through mathematical modeling of regulatory networks implicated in EMP; his work has featured on the cover of Journal of Clinical Medicine, Cancer Research, and Molecular and Cellular Biology, and he won the 2016 iBiology Young Scientist Seminar Series – a coveted award for communicating one’s research to a diverse audience. Currently, his lab focuses on decoding mechanisms and implications of non-genetic heterogeneity in cancer metastasis and therapy resistance, with specific focus on mechanism-based and data-based mathematical modeling in close collaboration with experimental cancer biologists and clinicians. He is an elected fellow of Indian National Young Academy of Sciences (INYAS), and serves as Secretary of The International Epithelial-Mesenchymal Transition Association (TEMTIA).

Event Photos: Day 2021 Jan 24 (Sunday)





























































################# COMPLETED ########################


 Dr. Durjoy Majumder
Organizing Secretary, SSBTR International Webinar Lecture Series