Molecular Simulations as an in silico Experiment – Seyit Kale

Presenter

Seyit Kale

Seyit Kale received his Bachelor of Science in Physics from İhsan Doğramacı Bilkent University in 2006, and his Ph.D. in Biophysics and Structural Biology from Brandeis University in 2012. He continued his postdoctoral studies at the University of Chicago, developing methods for computational chemistry. Later in 2015, he became a visiting fellow at the National Institutes of Health in Bethesda, Maryland, where he developed and pursued an interest in the physics of chromatin and epigenetics. He joined Izmir Biomedicine and Genome Center in late 2019 as a research group leader where he is currently running a lab in computational biophysics.

Abstract

Structural studies in biology provide invaluable insights into how molecular machines inside our cells look like, yet the stories are often far from over. The set of atomic coordinates of a macromolecule is like a picture: it’s worth a thousand words. Then again, a picture lacks the temporal information which underlies the dynamic personalities of the molecule. Over the last several decades, exponential growth in computing power drew increasingly more physical scientists toward questions of life sciences. Faster algorithms and more accurate interaction potentials have been developed to propagate the Newtonian equations of motion in length- and timescales relatable to biological phenomena. In this lecture, I will discuss an often frowned upon analogy, i.e., how a molecular simulation can be thought of as an in silico experiment, by providing a historical and physical perspective.

Date: March 5th, 2020 – 5:00 pm (GMT+3)

Language: English

To register the webinar, you can visit this link:
https://www.bigmarker.com/bioinfonet/Molecular-Simulations-as-an-in-silico-Experiment

RSG-Turkey is a member of The International Society for Computational Biology (ISCB) Student Council (SC) Regional Student Groups (RSG). We are a non-profit community composed of early career researchers interested in computational biology and bioinformatics.

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