Ravi Radhakrishnan

This study shows ECM stiffness enhances EGFR signaling through integrin-mediated membrane curvature and topography, affecting RTK signaling across scales and potentially explaining resistance to tyrosine kinase inhibitors.

This study investigates complement activation on nanoparticle surfaces, showing it exhibits criticality with diverging order parameters and a transport-limited mechanism.

This study develops a multiscale framework to analyze how cell-intrinsic and microenvironmental factors drive divergent trajectories in castration-resistant prostate cancer.

This study shows enzyme activity enhances ligand diffusion and receptor-mediated endocytosis by generating mechanical fluctuations in the extracellular matrix.

This study models how poroelastic properties of the extracellular matrix affect tumor growth and transport through hydrogel experiments and computational simulations.

Kinome-AI predicts activating kinase mutations using machine learning, achieving high accuracy without requiring structural inputs for new mutations.

The paper investigates how cells from different tissue types respond to changes in ECM mechanics and composition, finding significant heterogeneity and the role of HA in modulating cell mechanics.

The paper identifies a critical threshold in complement activation based on surface density, showing percolation-type behavior in immune responses to materials.

The paper identifies TRE motifs as indirect MYC binding sites that synergize with AP-1 at enhancers, leading to transcriptional rewiring in cancer.

This study identifies two mutation profiles in EGFR Exon-19 deletions that correlate with differential TKI sensitivity through analysis of conformational dynamics and solvent interactions.

The paper develops a multi-scale framework integrating cancer pathways to predict patient-specific treatment responses in prostate, lung, and kidney cancers.