Molecular biology

Proteins are the most important biomolecules for living
organisms. The understanding of protein structure, function, dynamics, and
transport is one of the most challenging tasks in biological science. We
have introduced persistent homology for extracting molecular topological
fingerprints (MTFs) based on the persistence of molecular topological
invariants. MTFs are utilized for protein characterization, identification,
and classification. Both all-atom and coarse-grained representations of

Most of my work is focused around a single (broad) question: How can
we use our understanding of human perception and artistic traditions
to improve our tools for communicating and data understanding? In
problems ranging from molecular biology to video editing, we are faced
with a deluge of data. In this talk, I'll survey some of the ways
we've tried to turn this problem into solutions. I'll discuss our
efforts in data visualization and multimedia, showing how we can use

Water molecules are ubiquitous in living organisms and have therefore been
viewed more as an environment for biomolecules rather than as a collection
of interacting molecules. Water molecules make up an integral part of
protein structures, while assisting in catalysis, providing stability and
controlling the plasticity of binding sites. In order to realistically mimic
the environment of biomolecules, molecular dynamics simulations are
routinely done in explicit water. Unfortunately, most of the computational

Continuum electrostatics methods have become increasingly popular due to their ability to provide approximate descriptions of solvation energies and forces without the expensive sampling required by all-atom solvent models. In particular, the Poisson–Boltzmann equation (PBE) provides electrostatic potentials, solvation energies, and forces by modeling the solvent as a featureless dielectric material and the mobile ions as a continuous distribution of charge.

Recent advances have dramatically advanced our understanding of cancer
at the molecular level. In turn, new therapeutic agents that target
specific molecular defects in cancer have been developed, though cancer
remains a significant health threat. Following an introduction to the
molecular biology of cancer, a statistical approach to distinguish
driver mutations from passengers based on non-random clustering will be
discussed. Next, approaches to pharmaceutical intervention will be

We will discuss superimposed codes and non-adaptive group testing designs arising from the potentialities of compressed genotyping models in molecular biology. The given survey is also motivated by the 30th anniversary of our recurrent upper bound on the rate of superimposed codes published in 1982.

In this talk, I will present our recent work in trying to understand bacterial chemotaxis (bacteria’s ability to sense and track chemical gradient) by using a quantitative modeling approach. Based on molecular level knowledge of the E. coli chemotaxis pathway, we propose a simple model for bacterial chemotaxis and use it to address several interesting, important system-level questions: 1) What kind of computation does a E. coli cell perform in response to complex time-varying stimuli? 2) What kind of memory does E. coli have? How long does it take the cell to forget?