Center for Computational Biology

Simons Foundation

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.

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.

Groups

Biophysical Modeling The Biophysical Modeling group focuses on the modeling and simulation of complex systems that arise in biology and soft condensed matter physics. Read More

Genomics 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. Read More

Neuroscience Our goal is to understand how the brain analyzes large and complex datasets streamed by sensory organs in order to aid efforts at building artificial neural systems and treating mental illness. Read More

Numerical Algorithms The Numerical Algorithms group develops new computational and statistical methods for the analysis of large, complex datasets and for the accurate numerical simulation of biological processes. Read More

Systems Biology At the Systems Biology group, we are developing new methods to learn the networks that run life’s program. Read More

News & Announcements

Particles Surf Their Own Waves, Reveal How Microbes and Cells Move Through Human Body

AI Accurately Predicts Effects of Genetic Mutations in Biological Dark Matter

Flatiron Hosts First MountainSort Users Workshop

Research Highlights

July 24, 2018

Classification with Joint Time-Frequency Scattering

J. Andén, Vincent Lostanlen, Stéphane Mallat

In time series classification, signals are typically mapped into some intermediate representation which is used to construct models. We introduce…

arXiv:1807:08869

July 16, 2018

Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk

J. Zhou, Chandra L. Theesfeld, K. Yao, K. Chen, A. Wong, O. Troyanskaya

Key challenges for human genetics, precision medicine and evolutionary biology include deciphering the regulatory code of gene expression and understanding…

Nature Genetics

July 2, 2018

GIANT 2.0: genome-scale integrated analysis of gene networks in tissues

A. Wong, Arjun Krishnan, O. Troyanskaya

GIANT2 (Genome-wide Integrated Analysis of gene Networks in Tissues) is an interactive web server that enables biomedical researchers to analyze…

Nucleic Acids Research

Director

Leslie Greengard, M.D., Ph.D.

Director, CCB

Leslie Greengard joined the Simons Foundation in 2013 as founding director of the Simons Center for Data Analysis, now called the Center for Computational Biology. Prior to that, Greengard served as director of the Courant Institute of Mathematical Sciences at New York University.

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