Graduate Students

Photo of ARZASH
My overall research interests include understanding the mechanical and dynamic properties of soft and biological materials. Biopolymers, as well as carbon nanotubes can be characterized as semiflexible polymers, which have been shown to exhibit elastic and relaxational properties that differ strongly from flexible polymers. By simulating networks of semiflexible polymers, we can predict their mechanical response, as well as the dynamics of their stress relaxation.
Photo of BONOMO
My research investigates modular structure and function in a variety of biological topics. In CRISPR-Cas, I model the kinetics of crRNA:Cas9 recognition of invading DNA to understand how modularity contributes to specificity and efficiency. In the human immune system, I model vaccine efficacy against influenza based on antibody recognition of modular sites on the virus's hemagglutinin protein. In the human brain, I analyze network modularity in fMRI data of people listening to music to work towards personalizing music therapy. I also model brain network changes that lead to cognitive impairment and analyze MEG data from patients with dementia.
photo of BUENO
The goal of my work is to improve the models used to predict the stability of proteins. I use several methods including direct coupling analysis, the AWSEM forcefield and normal mode analysis. The insights obtained by these analyses can also be used to analyze the movement of the protein during allosteric regulation.
photo of CHEN
I’m interested in dynamic properties of soft materials such as semiflexible biopolymers. Currently, I’m working on non-equilibrium force generation in actin filaments.
Photo of XUN
My research mainly focuses on the dynamics of protein and DNA in vivo, included protein aggregation, protein-DNA interaction and membrane protein. The transition of molecular structure in vivo determine their function in human life. I want to use physical tools to understand these kind of action better. At the same time, I am also interested in develop the Hamiltonian of AWSEM model to describe the protein folding, which also can help us understand the protein function better.
photo of COLEMAN
My work focuses on modeling the cell-fate decision in bacteriophage lambda. My goal is to quantitatively describe the gene expression kinetics of the lambda decision and to identify and characterize the main factors that drive it.
Photo of Lucas
My overall research interest is in the mechanical behaviour of complex fluids in the microscale. In the past years, I have worked with numerical simulations of droplets flowing through microchannels and magnetic droplets under the influence of external magnetic fields and imposed flows. Recently, I got interested in the use of chains of magnetic colloidal particles as tools to understand the rheological response of biological materials.
photo of DENG
My research concerns efforts in modeling the couplings between the mechanics of ECM (extra-cellular matrices) and biology of cells embedded inside the former.
photo of DENG
My research mainly focuses on computational methods and their application on biosystems. Currently, I am working on the behavior of a certain kind of RNA called riboswitch via SMOG forcefield and other methods developed by our group.
photo of ELIAZ
We seek to understand the physics of living systems. Specifically, I study the theory of active matter inside a cell. I am highly interested how actomyosin networks evolve and store information as mechano-biological machines. By harnessing ideas from computer science and applied mathematics, we aim to explain the physical principles of self-assembly in biological matter. The end goal is to elucidate how long-term memory is formed and maintained.
photo of GALBRAITH
I'm interested in the mechanism of cancer metastases and pathways that can be targeted to slow/stop cancer growth. My research focuses on using mathematical models of the gene networks involved, such as the notch signaling pathway.
Inside a living cell, there is an immensely complex and crowded environment—this is far from the ideal test-tube setting. Our understanding of how proteins and other biomolecules function in this environment is largely unknown. Using both theory and computer simulations, my research aims to answer important questions at the interface of physics and biology, spanning from the single protein scale to cellular scales. The thrusts of my research consists of understanding the following: i.) the effects of the cellular environment on protein folding; ii.) criticality of proteins and the effects of macromolecular crowding; iii.) the physics of hierarchical protein-complex assemblies and the "structure" of the
photo of GU
I'm interested in computational and theoretical chemistry, especially in topics about biological systems, like proteins. My recent research direction aims at improving protein structure prediction, basing on AWSEM coarse grain model.
Photo of HRUSKA
My research focuses on the analysis of macromolecular dynamics and the development of new strategies for enhanced sampling. Current methods for adaptive sampling are mostly based on dimensionality reduction tools, but the speed-up achieved for complex systems is still limited. Analyzing the shortcomings of the current methods allows us to improve these methods and develop new approaches, in order to better simulate and characterize protein dynamics over long timescales.
Photo of JAAFARI
My research interests center on employing computational modeling and theoretical physics to explore the dynamics of biological systems. I currently study the role evolution plays on the energy landscapes of proteins by examining pseudogenes, using our AWSEM coarse grain model and DCA model.
Photo of JIA
My research mainly focuses on cancer system biology. Transitions between epithelial and mesenchymal phenotypes play important roles in both tissue repair and cancer metastasis. Currently, I’m investigating the influences of new feedback terms on EMT and MET. Some would have significant effects on the transitions and need to be further studied.
photo of Jin
My research interests include protein structure prediction and application in solving crystallographic phasing problem. The phasing problem, which arises from the fact that X-ray diffraction experiments only record the intensities, but not the phases, of the diffracting electromagnetic waves. With de novo predicted structure, we can solve phasing problem by molecular replacement and get real structure from X-ray data. This method will greatly broadens the protein structure database.
My research focuses on understanding the role of calcium-binding proteins in regulating actomyosin networks using coarse-grained models and physics-based approaches.
Photo of KLUBER
My research investigates how the essential physics regulating macromolecular dynamics and function can be captured in coarse-grained models. I am exploring new strategies to design coarse-grain models by considering new functional forms and by incorporating experimental measurements in the simulation.
Photo of KNAPP
My research interests include computational modeling and analysis of biomolecular dynamics and applications of machine learning. I am particularly interested in coarse-grained network modeling and the interplay of flexibility and frustration in the large scale conformational changes that accompany biomolecular functions.
I am interested in polymer behavior in biological systems using theory and simulation techniques. Theoretical understanding of semiflexible polymers can be used to predict and explain the behavior of actin filaments that constitute the cytoskeleton in cells. Currently, my research focuses on studying the stress relaxation in actin filament networks.
My research focuses on coarse-grained modelling of active networks in biological systems and investigating the impact of actin-binding proteins on actomyosin network dynamics.
Photo of LIMAN
I am currently working on understanding long-term morphological plasticity of dendritic spines by computationally integrating known short-term biochemical signals and actin cytoskeleton reorganization. This study, when successful, will considerably advance our understanding of cellular mechanism of learning and memory.
Photo of LU
Membrane proteins account for more than 20 percent of all human protein-coding genes and more than 50 percent of the drug targets using today. My current research focuses on the studying of force induced membrane protein unfolding dynamics using our coarse grain model (AWSEM).
Photo of WEIQI LU
My research interests include the modeling and computational simulation and analysis of biomolecular architecture. Currently, I am mainly focussed on the chromosome conformation, to be more specific, how the Minimal Chromatin Model (MichroM) would work on higher-ordered contacts within a single chromosome.
My research involves the Prediction of Actin-Actin interactions via co-evolutionary sequence analysis and molecular dynamics simulation.
My research is focused on understanding how robust cellular mechanisms evolve at the mesoscale from noisy molecular level structure and dynamics of biopolymers. A major challenge in probing a living cell is its highly heterogeneous and crowded environment. To this end, a combination of bottom-up approaches such as coarse-grained theoretical modeling and single molecule force-extension experiments have helped capture the generic features of semiflexible biopolymers (for example DNA, actin bundles) and elucidate key biological questions. I apply mean-field theory together with computation to study the effects of variable tensile forces like electrophoretic stretching on the statistics and rheology of charged biopolymers (polyelectrolytes). The aim is to explain the eventual consequences of non-uniform tension on biologically relevant processes like DNA-histone packaging.
I am interested in studying biophysical systems by means of theoretical and computational methods. My current research topics include the development of a novel stochastic model that describes the mechanism of antimicrobial peptides on bacteria.
My project is the study of dynamics and aggregation of tumor suppressor protein p53 (wild type and mutants) using molecular modeling, investigation of mechanisms of dense liquid condensates formations and its role int he nucleation and growth of amyloid fibrils.
My objective is to develop a theoretical model to understand the principles of emerging protein-complex assemblies in signalling pathways using a statistical mechanical framework.
photo of SHIVERS
I am interested in the elastic properties of semi-flexible polymer networks. In living systems, such networks provide striking nonlinear mechanical behavior to cells and tissues, including strain stiffening and negative normal stresses. Currently, I am working to characterize the dependence of negative normal stress on network structure and applied strain.
Photo of TINNIN
My research focuses on understanding the structure-function relationship of organic photovoltaic materials. Currently we are focusing on electron donor-acceptor heterojunctions such as C60-SubPC and C70-DBP. We model the interface using molecular dynamics and obtain significant structures using statistical mechanics and machine learning techniques. We then compute charge transfer statistics using quantum chemistry and link this to device performance using a kinetic Monte Carlo method. This link between interfacial geometry and device performance is up-to-now unknown and will allow for the creation of improved solar technology.
I am interested in studying the dynamics of evolution in heterogeneous and changing environments, using stochastic simulations, physical principles, and mathematical models. Of particular interest are the emergence of antibiotic resistance in bacteria and the emergence of drug resistance in cancer cells. I am also interested in understanding the general theoretical principles governing biological evolution and how these can be applied in a clinical setting, for example, in cancer prognosis.
photo of YAO
I am a graduate student in the department of Biochemistry and Molecular Biology at Baylor College of Medicine, working in the lab of Dr. Ido Golding. I am working on the system comprising the bacterium E. coli and phage lambda. My goal is to discover the undetected variables that contribute to the heterogeneity of lambda gene expression and the resulting decision between lysis and lysogeny.
photo of YE
My research focuses on quantitative modeling of complex biological systems. Such systems include gene interaction networks in cancer cells, functional connectivity in human brain, genome-scale metabolic network of E.coli, and so on. I use methods such as network clustering, dimensionality reduction, neural networks, and flux balance analysis. The overall goal of my research is to understand the relation between the structure and function of biological networks.
photo of ZHANG
My primary research interest centers on applying multi-disciplinary models into biological research. I am taking advantage of deep learning to transfer phase-contrast images of Myxococcus xanthus into fluorescent images, which can be easily interpreted to cell density maps. I am also working on extracting Myxo cell aggregation features, which will be helpful to cluster mutant strains into different genetic pathways.