The Center for Computational Biology develops new and innovative methods of examining data in the biological sciences whose scale and complexity have historically resisted analysis.
In using AI-powered tools to map proteins in the human gut microbiome, researchers have challenged the traditional view of the relationship between protein sequence, structure and function.
CCB’s mission is to develop modeling tools and theory for understanding biological processes and to create computational frameworks that will enable the analysis of the large, complex data sets being generated by new experimental technologies.
News & Announcements
April 28, 2023
April 03, 2023
March 13, 2023
Meeting 10:30 - 11:30 a.m.
Developmental Dynamics Group Meeting
- Meeting 10:30 - 11:30 a.m.
Meeting 10:00 a.m. - 12:15 p.m.
Biophysical Modeling Group Meeting
- Meeting 10:00 a.m. - 12:15 p.m.
Meeting 11:30 a.m. - 1:30 p.m.
Genomics Group Meeting
- Meeting 11:30 a.m. - 1:30 p.m.
Ensemble reweighting using Cryo-EM particles
Cryo-electron microscopy (cryo-EM) has recently become a premier method for obtaining high-resolution structures of biological macromolecules. However, it is limited…arXiv:2212.05320
Concurrent ARFI Plaque Imaging and Wall Shear Stress Measurement in Human Carotid Artery, with Validation by Fluid Structure Interaction Model.
The rupture potential of an atherosclerotic plaque is dependent on both the plaque’s composition and the shear stresses it encounters…IEEE International Ultrasonics Symposium
SARS-CoV-2 Outbreak Dynamics in an Isolated US Military Recruit Training Center With Rigorous Prevention Measures
Marine recruits training at Parris Island experienced an unexpectedly high rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection,…Epidemiology
This is the simulation tool for tracking assemblies of microtubules driven by motor proteins.
This is a numerical computation package for various single- and double-layer kernels for Laplace and Stokes operators in boundary integral methods, implemented on top of the highly-optimized kernel independent fast-multipole method package PVFMM.
Data-driven predictions of gene expression, function, regulation, and interactions in human.
Deep learning-based algorithmic framework for predicting chromatin effects
Functional Networks of Tissues in Mouse
Genome-wide Scale functional interaction networks for 144 human tissues and cell types
Integrative Multi-species Prediction
K-Nearest Neighbors Imputation
This server performs in silico nano-dissection, an approach we developed to identify genes with novel cell-lineage specific expression.
Search-Based Exploration of Expression Compendium [Human]
SkellySim is a simulation package for simulating cellular components such as flexible filaments, motor proteins, and arbitrary rigid bodies.
Sleipnir Library for Computational Functional Genomics
A data-driven perspective to your gene expression profile for human tissues and diseases.