Key challenges for human genetics, precision medicine and evolutionary biology include deciphering the regulatory code of gene expression and understanding…Nature Genetics
An immensely complex molecular network of interactions forms the foundation of human biology and disease. Genomic approaches provide a particularly illuminating window to biological systems, and when combined with advanced analysis allow us to learn and model this complexity.
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.
GIANT2 (Genome-wide Integrated Analysis of gene Networks in Tissues) is an interactive web server that enables biomedical researchers to analyze…Nucleic Acids Research
Genome-wide prediction and functional characterization of the genetic basis of autism spectrum disorder
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with a strong genetic basis. Yet, only a small fraction of…Nature Neuroscience
Xi Chen joined the Flatiron Institute’s Center for Computational Biology in 2016 in the genomics group. Chen’s research focuses on developing algorithms for processing and statistical analysis of heterogeneous genomics data. He has a Ph.D. in electrical engineering from Virginia Polytechnic Institute and State University,…
John Hayward joined the Simons Foundation in 2016 as a senior software engineer in Center for Computational Biology’s Genomics group. Before joining the foundation, Hayward worked as a research and development analyst for the Bloomberg Tokyo Marunouchi office, adapting East Asian market data feeds for…
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