Akza Ahmed, Graduate Student, University of Wisconsin, Madison
 My work in May-MIDAS lab focuses on developing in silico models to study the combined effect of vitamin D3 and alcohol metabolism on modulation of key inflammatory cytokines and effector molecules produced by macrophages during Mycobacterium tuberculosis (Mtb) infection. More specifically, the mathematical model is formulated in MATLAB using a system of ordinary differential equations (ODEs) to depict signal transduction pathways that arise from Mtb lipoarabinomannan (LAM) activation of pro and anti-inflammatory cytokines such as IL-12, IFN-y, IL-10, and effector molecules including H2O2 and NO. A current project in our lab involves developing regression-based models for existing experimental data and determining cell death pathways in murine macrophages.
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Aviva Presser Aiden, Assistant Professor, Baylor College of Medicine
I am working on multiple aspects of 3D-genomics. I am using these tools to explore how structural factors affect different organs’ development. I am also using these tools to explore mosquito and blood meal genomics, and metagenomics/diagnostics applications.
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Vinicius Contessoto, Postdoctoral Scholar, Rice University
 My research centers on the development and application of theoretical biophysics models combined with computational simulations to investigate the dynamics and function of chromosomes and proteins. I’m particularly interested in understanding structural changes in chromosomes throughout the cell cycle and the interplay between chromatin organization and gene expression. Additionally, I explore protein folding and engineering, with a focus on computational methods for predicting epitopes in immunization strategies and identifying mutations that enhance enzyme thermostability.
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Max Hall-Brown, Graduate Student, Rice University
 My work centers generally on the cytoskeleton, and more specifically on how material and structural properties can emerge in biological context. Central to this problem are ideas borrowed from the physics of amorphous glassy materials, which have a complicated and intricate set of behaviors in their own right. These ideas are useful for understanding systems such as biomolecular condensates, actin-myosin networks, the dendritic spine, protein folding, and many others. I’ll mostly work on biomolecular condensates and actin-myosin networks in the near future, as well as more fundamental physics work in the field of glasses.
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Praveen Kumar, Postdoctoral Scholar, Northeastern University
 I am interested in a wide range of soft matter physics problems, spanning both biological and non-biological systems. My current research interests are focused on comprehending the mechanics and collective behaviors in biological tissue systems through the use of theoretical modeling and computer simulations. I apply tools from statistical and soft matter physics to understand and predict emergent phenomena in these dynamic systems.
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Matheus Mello, Graduate Student, Rice University
 My work focuses on genome organization and chromosome structure and dynamics. Using coarse-grained theoretical models, I study the organization of the chromosomes in the nucleus, how chromosomes interact, and how active and inactive chromatin phase-separates in the nuclear environment. I am also interested in the interaction of chromatin with other nuclear bodies and in the chromosome structural changes over the cell cycle.
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Ronaldo Oliveira, Postdoctoral Scholar, Rice University
 We’ve been working on problems related to protein folding dynamics and chromatin organization. These studies primarily involve molecular dynamics simulations of coarse-grained models, through which we characterize the kinetics and thermodynamics of the biomolecules under investigation. Recently, our focus has shifted to studying the association mechanism between two intrinsically flexible proteins and exploring the minimal chromatin model.
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Christina Palma, Postdoctoral Scholar, Rice University
My work focuses on gene regulatory mechanisms that allow bacteria to adapt and survive to stress conditions. For this, I combine computational methodologies, including stochastic and deterministic models, statistics, and signal processing techniques, with experimental data obtained from a spectrum of techniques such as microscopy, flow-cytometry, and RNA-seq. Specifically, I study the cellular adaptation mechanisms, on a systems level, by focusing on different regulatory factors such as transcription factors, DNA supercoiling and post-translational interactions.
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Daniel Ramirez, Graduate Student, Northeastern University
 My research focuses on combining mathematical modeling and bioinformatics to construct, refine, and simulate gene regulatory networks, in particular concerning cellular state transitions. Among other tools, we use stochastic differential equations, single-cell transcriptomics, and machine learning approaches to study processes including the cell cycle and epithelial-mesenchymal transition. Eventually, our aim is to create data-driven dynamical models to understand the fundamentals of cellular information processing.
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George Wanes, Graduate Student, Northeastern University
 My research focuses on using molecular dynamics in studying the energy landscape of biomolecules based on structure-based models. Currently, I am working on developing a model that can capture the effects of the ions on the dynamics of large-scale assemblies, including the ribosome.
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Douglas White, Graduate Student, Northeastern University
Chromatin is an amalgam of DNA and proteins within a cell’s nucleus. I model chromatin with course-grained polymers, each bead of which represents a segment of DNA. To do this, I use molecular dynamics to sample a free energy landscape of 3D structures. I would also be interested in applying statistical mechanical methods and abstract math to the nucleus and beyond. Wild ideas beyond the scope described above are welcome as well; the wilder the better.
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Yukai You, Graduate Student, Northeastern University
 My research seeks to unravel the complexities of cellular state transitions, such as differentiation and immune activation, by constructing precise gene regulatory networks through nonlinear ordinary differential equations, leveraging single-cell genomics data. My approach aims to enhance our comprehension of cellular behaviors and their continuous dynamics, offer deeper insights for potential therapeutic developments, and provide a robust understanding of life’s fundamental biological processes.
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