Computational Biology: Software & Datasets

Simulates microtubule assemblies with motor proteins using Monte Carlo dynamics, constrained collision handling, and massive parallelization.

Uses deep learning to predict chromatin effects of DNA variants, including TF binding, DNase sensitivity, and histone marks across cell types.

Uses tissue-specific gold standards to build functional gene networks, prioritizing relevant data and enabling cross-tissue gene interaction comparisons.

Builds tissue-specific gene networks, enables cross-tissue functional comparison, and reprioritizes GWAS signals to identify disease-associated genes.

Uses machine learning on large genomic datasets to discover new biological gene associations beyond existing literature knowledge.

Analyzes experimental results using cross-species gene networks to reveal functions and guide new experiments identifying gene–pathway roles.

Imputes missing microarray data using k-nearest neighbors, shown to perform well compared to other missing-value estimation methods.

C++ macromolecular modeling libraries aiming to replace Rosetta, leveraging modern CPUs/GPUs and quantum hardware for NP-hard optimization tasks.

A C++ infrastructure for building scalable, biologically grounded microscale multibody dynamics software.

Performs in silico nano-dissection to identify cell-lineage–specific genes using functional genomics data from tissue samples.

Probability Flow Inference (PFI) is a framework for inferring gene-regulatory dynamics from time-stamped cross-sectional omics data, where cells are measured destructively and cannot be tracked …

Protein modeling and design software extended to support noncanonical amino acids, enabling prediction and design of mixed-chirality peptide macrocycles.

Gene co-expression search engine that ranks genes and datasets from large expression compendia using multi-gene queries and cross-platform analysis.

Scalable simulation package for cellular components using parallel computing and fast hydrodynamic methods for filaments, motors, and rigid bodies.

C++ library for fast genomic data integration, mining, and ML across large datasets, with tools for microarrays and other biological data types.

Fast boundary integral kernels for Laplace and Stokes equations using optimized fast multipole methods and AVX2 SIMD acceleration.

Identifies tissue and disease signatures from gene expression data using large-scale profiles, enabling molecular analysis of submitted samples.