Research
The long genome —roughly one meter of DNA in a human cell — is severely compacted to fit inside a nucleus only about ten microns across. Rather than collapsing into a featureless globule, it self-organizes into a rich hierarchical structure: chromosomes occupy separate territories, open and closed chromatin form interspersed compartments, and topological domains partition the chromosome at the megabase scale. Research in the Brahmachari Lab is grounded in the polymeric nature of the genome, modeling living DNA as a twistable, semiflexible polymer in which protein-mediated kinks and bends act as sources and sinks of bending and twisting energy. Our goal is to learn the physics of the active mechanisms that drive genome folding and to decipher the regulatory code of the living genome. The lab pursues three connected directions:
A central direction of the lab is energy landscape modeling. We construct energy landscape models grounded in statistical mechanics to understand how proteins — particularly cohesin-mediated loop extrusion — together with phase separation and lamina adhesion drive genome organization. These frameworks integrate molecular dynamics simulations with experimental Hi-C and imaging data to connect chromosome structure to function.
A second direction concerns the active mechanisms that operate far from equilibrium. Living cells are inherently out of equilibrium: motor proteins consume energy to remodel chromatin, RNA polymerases twist DNA as they transcribe, and correlated active forces drive chromosome dynamics. We develop theoretical and computational frameworks to study active forces, motor-driven loop extrusion, torsional-stress propagation from transcription, and how non-equilibrium fluctuations shape genome organization and gene regulation.
A third direction develops physics-based AI. Purely data-driven AI models lack physical interpretability, while purely physics-based models struggle to capture the complexity of biological systems. We build AI models grounded in physical principles — incorporating known symmetries, conservation laws, and mechanistic constraints — to predict genome structure, infer model parameters from experimental data, and generate physically meaningful insight.

Representative Recent Publications
S. Brahmachari, A. B. Oliveira Jr., M. F. Mello, V. G. Contessoto, and J. N. Onuchic. Exploring the Energy Landscape of Bacterial Chromosome Segregation. Proc. Natl. Acad. Sci. USA, 2026.
J. Hwang, C.-Y. Lee, S. Brahmachari, S. Tripathi, T. Paul, H. Lee, A. Craig, T. Ha, and S. Myong. DNA Supercoiling-Mediated G4/R-loop Formation Tunes Transcription by Controlling the Access of RNA Polymerase. Nature Communications, 2025.
S. Brahmachari, S. Tripathi, J. N. Onuchic, and H. Levine. Nucleosomes Play a Dual Role in Regulating Transcription Dynamics. Proc. Natl. Acad. Sci. USA, 2024.
S. Brahmachari, T. Markovich, F. C. MacKintosh, and J. N. Onuchic. Temporally Correlated Active Forces Drive Segregation and Enhanced Dynamics in Chromosome Polymers. PRX Life, 2024.
C. Hoencamp, A. M. O. Elbatsh, O. Dudchenko, S. Brahmachari, et al. 3D Genomics Across the Tree of Life Reveals Condensin II as a Determinant of Architecture Type. Science, 2021.
S. Brahmachari and J. F. Marko. Chromosome Disentanglement Driven Via Optimal Compaction of Loop-Extruded Brush Structures. Proc. Natl. Acad. Sci. USA, 2019.
A complete, up-to-date publication list is available on the lab publications page.