Juan Pablo

CRANBERRY is a coarse-grained RNA model that includes sugar puckering and noncanonical base pairing, achieving performance comparable to all-atom models in structural predictions and experimental agreement.

The paper develops a framework combining polymer physics and machine learning to estimate chromatin structures from Hi-C data with high accuracy.

This study theoretically examines how intranuclear factors like salt concentration and pH affect the charge state of nucleosome core particles, highlighting the role of magnesium ions and molecular details.

This paper introduces OpenAWSEM and Open3SPN2, GPU-accelerated coarse-grained simulation tools for proteins and DNA, enabling faster and more flexible modeling of biomolecular systems.

The paper introduces a nano-ChIA platform that combines electron tomography and superresolution imaging to study chromatin structure and dynamics at the single-nucleosome level in live cells.