Dave Thirumalai

This study shows that spermine induces two phase transitions in ssDNA through stacking and electrostatic interactions, with sequence-dependent behavior.

This study uses molecular simulations to show how RNA sequence patterns drive aging and spatial organization in biomolecular condensates, revealing structural changes that lead to dynamic arrest.

This study uses agent-based models to analyze how normal and cancer cells respond to shear stress, finding that heterogeneity in stiffness and activity leads to non-affine movements.

The paper uses simulations to calculate the persistence length of short ssDNA homopolymers in polyvalent cations, finding it depends on the inverse Debye length and is largely independent of spermine concentration.

The paper develops a theory to explain condensin's forward and backward steps during loop extrusion, revealing catch bond-like behavior under mechanical force.

The paper develops an AMC model to link multiway enhancer-promoter contacts and enhancer activity to gene overexpression in prostate and breast cancer.

This study investigates the phase separation and assembly of FUS-LC, showing that core regions form in a specific order and that Ostwald's rule applies to their maturation and stability.

This study develops a theory to infer locus-specific chromatin viscoelasticity from 3D genome organization and finds that mechanical properties are determined by both chromatin epigenetic marks and organization.

This study investigates rotational migration in human pancreatic ductal organoids, showing it depends on actin and myosin activity through inhibition experiments.

The paper investigates how lever arm flexibility affects coupling to the motor domain in dimeric myosin motors using theoretical models and chimeric constructs.

The paper models biomechanical feedback during zebrafish embryogenesis to predict the transition from synchronous to asynchronous cell divisions and explains the resulting cell cycle lengthening.

This study shows that RNA structural flexibility influences its ion atmosphere, with unstructured RNAs having diffuse ion clouds that extend further than folded RNAs.

The paper develops a theory to predict chromatin dynamics using static 3D structures, showing that fast enhancer-promoter dynamics and scaling relationships are determined by chromatin organization.

The paper shows that a nematic liquid crystal state forms during gastrulation in fish, frogs, and fruit flies through a common mechanism, with experimental and theoretical support.

This study identifies how disulfide bond formation during glutenin subunit folding drives the polymerization into linear or branched gluten networks.

This study shows water-mediated interactions between neutral N-glycans are weakly repulsive and long-ranged, with decay following a logarithmic pattern.

This paper develops a 3D model to study tissue morphologies and dynamics by varying cell size, elasticity, and self-propulsion, revealing distinct phases and behaviors.

This study uses agent-based simulations to show that mechanical feedback from cell division and proliferation influences cell dynamics in growing tissues, with distinct diffusion behaviors depending on feedback strength and growth rate.

This study investigates how Guanidine Hydrochloride affects the structural behavior of two intrinsically disordered proteins using simulations and SAXS profiles.

The paper develops a genetic algorithm to study how synonymous mutations affect mRNA structure and reveals a physical code in the genetic code that influences RNA-protein complex properties.

This paper uses simulations to show that sequence complexity and monomer rigidity determine the morphology and aging dynamics of protein aggregates.

The paper shows that RNA folding in germ granules limits intermolecular base pairing, which is essential for normal fly development.

The paper shows that salt concentration affects RNA self-association rates and yields through changes in free energy gaps, with implications for repeat RNA aggregation.

The paper develops a computational model to study ion-DNA interactions and shows it accurately predicts experimental results without parameter tuning.

This study shows that hydrodynamic interactions are essential for accurately simulating kinesin's stepping kinetics, as their exclusion leads to drastically reduced stepping efficiency.