Lina is applying mathematics and information theory to systems biology and bioengineering. She works on a collaborative project with bioinformaticians and biochemists in Bioengineering at University of California, San Diego through the Center for Science of Information (CSOI). Aside from her research interests, Lina is passionate about science communication and outreach initiatives. Much of her previous undergraduate and graduate work at Vanderbilt and Cornell were and continue to be centered around involvement in developing and enhancing K-12 STEM outreach programs. This is an initiative in which she is working to include computer science based lessons and activities.
Parul joined our research group in Fall 2014 as graduate research assistant. She is working on chemotherapy induced peripheral neuropathy, which is a prevalent side effect arising due to many chemotherapy drugs. She is working on predicting which patient is susceptible to peripheral neuropathy, using patient data collected by clinicians at Riley hospital, Indianapolis, and profiled by Bindley Bioscience Center. She uses various machine learning algorithms to analyze patient data.
In another project, she is analyzing a mathematical model of a single sensory neuron to investigate how chemotherapy drugs induce peripheral neuropathy. She is using computational neuroscience and dynamical systems tools to understand the role of voltage gated ion channels in the excitability of a neuron. This project is in collaboration with researchers from Max Planck Institute, Germany, and Purdue Institute for Integrative Neuroscience.
Akancha joined our research group in Fall 2014 as graduate research assistant. She is working on the model based optimal dosing strategy for sickle cell disease.
Pelin Su Bulutoglu
Pelin joined our research group in Fall 2017 as a graduate research assistant. She is working on polymorph prediction by using molecular dynamics simulations to calculate polymorph specific nucleation rates. Following the work of Conor Parks based on Critical Nucleation theory (CNT) on molecular simulations data, Pelin is investigating the extension of nucleation scenarios more detailed than CNT to predict nucleation rates and other polymorph-specific properties.
Sana joined our research group in Fall 2019 as a graduate research assistant. She did her Bachelor’s and Masters’ in Chemical Engineering from the Indian Institute of Technology (IIT) Kanpur, India. She will be working on cybernetic modeling of inflammatory systems. While cybernetic models have primarily focused on bacterial systems in the past, in our most recent work we adapted the framework to model the dynamic behavior of prostaglandin formation during the inflammatory response of bone arrow derived macrophages in mammalian systems. This work was based on hypothesizing that the system goal is to maximize TNF-alpha. This research is in collaboration with the with the research group of Professor Shankar Subramaniam in Bioengineering at UCSD. Sana will expand the cybernetic goal of the system to include combinations of multiple pheonotypic objectives subsumed into one optimal cybernetic goal for an organism using the maximization of mutual information between the weighted time series metabolite data and weighted combinations of multiple time series of transcriptomic data.
Post Graduate Researchers
Rubesh joined our research group in May 2019 as a postdoctoral research associate. He has completed his Ph.D. at Indian Institue of Science, Bangalore, India and his bachelors at National Institute of Technology, Tiruchirappalli, India. His research interests are biomathematical modeling, immunology, and infectious diseases.
Here, he works on a collaborative project with Prof. Shankar Subramanium at the Bioengineering department of the University of California, San Diego and Prof. Ananth Grama at the Computer Science department of the Purdue University. His project is to explore the cybernetic approach to modeling regulation in immune response cells such as Macrophage. The approach will be based on expanding the cybernetic goal of the system to include multiple phenotypic objectives subsumed into one optimal cybernetic goal for the organism using information theory.