The goal of CCB Genomics research is to interpret and distill this complexity through accurate analysis and modeling of molecular pathways, particularly those in which malfunctions lead to the manifestation of disease. We are inventing integrative methods for systems-level pathway modeling through integrative analysis of genome-scale datasets.
Two major hurdles in chimeric antigen receptor (CAR) T cell therapy for solid tumors are ensuring specificity to tumor cells…
Science Translational MedicineSystematic study of tissue-specific function of enhancers and their disease associations is a major challenge. We present an integrative machine-learning…
Cell SystemsTo enable large-scale analyses of regulatory logic in model species, we developed DeepArk, a set of deep learning models of…
Genome Research
Genome-wide Scale functional interaction networks for 144 human tissues and cell types
Deep learning-based algorithmic framework for predicting chromatin effects
This server performs in silico nano-dissection, an approach we developed to identify genes with novel cell-lineage specific expression.
Integrative Multi-species Prediction
Search-Based Exploration of Expression Compendium [Human]
K-Nearest Neighbors Imputation
Functional Networks of Tissues in Mouse
A data-driven perspective to your gene expression profile for human tissues and diseases.
Data-driven predictions of gene expression, function, regulation, and interactions in human.
Sleipnir Library for Computational Functional Genomics
