This virtual mini symposium showcased a diverse set of exciting studies in different areas of computational biology and highlighted how computational and theoretical ideas can lead to new biological insights and results. Included in this symposium were many different computational biology approaches, from mathematical models to machine learning. eLife publishes studies that use computational methods, models and software to provide important biological insights in all areas of the life sciences.
The one hour symposium featured four short talks from leading researchers in this subject area and was hosted by eLife Senior Editor, Aleksandra Walczak of Ecole Normale Supérieure in France. A Q&A with the speakers concluded the session.
eLife Senior Editor
Ecole Normale Supérieure, France
Aleksandra Walczak received her PhD in physics at UCSD working on models of stochastic gene expression. After a graduate fellowship at KITP, California, she took up a fellowship at the Princeton Center for Theoretical Science, focusing on applying information theory to signal processing in small gene regulatory networks. Currently she is a CNRS researcher at the Ecole Normale Superieure in Paris, interested in a variety of problems in the physics of living systems. She actively works on development, collective behavior of bird flocks and statistical descriptions of the immune system.
NSF-Simons Postdoctoral Fellow at Harvard University, Cambridge, USA
Gautam received his doctorate in Physics from UC San Diego. His work has largely focused on two aspects of computational neuroscience: algorithmic aspects of animal behavior & the neurobiology of mammalian olfaction. In past work, he has studied how birds navigate thermals in the atmosphere, how animals find food or mates using olfactory cues and how sensory systems extract useful task-relevant information from a complex stimulus. Broadly, he is interested in how biological systems make decisions under various constraints imposed by physical laws, physiology, and the limits of computation. Since 2019, he has been a Fellow at the NSF-Simons Center for Quantitative Biology at Harvard University.
Friedman Brain Institute at the Icahn School of Medicine at Mount Sinai in New York, USA
Kanaka Rajan, Ph.D. is a Computational Neuroscientist and Assistant Professor at the Friedman Brain Institute at the Icahn School of Medicine at Mount Sinai in New York. Her research seeks to understand how important cognitive functions — such as learning, remembering, and deciding — emerge from the cooperative activity of multi-scale neural processes. Using data from neuroscience experiments, Kanaka applies computational frameworks derived from machine learning and statistical physics to uncover integrative theories about the brain that bridge neurobiology and artificial intelligence.
Erik van Nimwegen
University of Basel, Switzerland
Prof. Erik van Nimwegen is Professor in Computational Systems Biology at the Biozentrum (Centre for Molecular Life Sciences) of the University of Basel in Switzerland. He heads a research group who apply theoretical and experimental approaches to study the function and evolution of the regulatory networks that cells use to control the expression of their genes.
Institute of Biology of the Ecole Normale Supérieure, Paris, France
After training in mathematics, Hélène did a Masters and PhD in ecology in France and then spent 5 years ½ as a postdoctoral researcher in ecology and evolution at UC Merced, the UO Eugene, UPenn and UC Berkeley. Hélène is now a CNRS research director at the Institute of Biology of the Ecole Normale Supérieure and her lab is interested in understanding how historical and contemporary processes shape present-day patterns of biological diversity.
Questions and comments are welcome. Please annotate publicly on the article or contact us at hello [at] elifesciences [dot] org.