The NSF-Simons National Institute for Theory and Mathematics in Biology is proud to announce the Institute has awarded funding to support ten new internal research projects. These projects are developing mathematical frameworks that illuminate emergent capabilities of biological systems. Explore a selection of the newly-supported research projects below. Additional details are available on the Supported Research page.
A new mathematical framework for classification in cell state dynamics
Principal Investigators: Yogesh Goyal (Assistant Professor, Cell and Developmental Biology, Northwestern University) and Suriyanarayanan Vaikuntanathani (Professor, Department of Chemistry, University of Chicago).
Abstract: Our proposal emerges from a crucial challenge in cell biology: how do transcriptionally identical cells make different fate decisions when exposed to therapeutic drugs? We have observed that while cancer cells may appear homogeneous, they can develop remarkably diverse resistance trajectories when treated with drugs. To address this fundamental question, we propose developing new mathematical tools that unite concepts from statistical mechanics of deep neural networks, non-equilibrium statistical mechanics, and information theory to understand how biological networks function as classifiers. Our work extends our recent findings showing how biochemical networks' classification capacity can be systematically tuned through factors like input promiscuity. We anticipate that this ambitious undertaking will establish a mathematically consistent framework for defining cell states and their transitions, elucidate the minimal requirements for biological networks to classify perturbations, and create predictive tools for cellular responses to therapeutic interventions.
Form and Function of Drifting Olfactory Representations in the Piriform Cortex
Developing a mathematics for evolved systems
Invasions in a Four-Species Cyclically Competing Ecological Community
Adaptation and Evolvability through Reinforcement Learning
Modeling RNA sequence-structure-function relationships with multiscale higher-order graph neural networks
Uncovering the link between chromatin organization and global transcriptional regulation
Characterizing excitability and its applications to immunity
Applications of the free probability to the diversity of response and variability in neuronal networks
Multimodal Data Analysis for uncovering host-microbiome responses to environmental stress