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

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

DNA ‘Dances’ in First Explanation of How Genetic Material Flows Through a Nucleus

An Integrative Tissue-Network Approach To Identify and Test Human Disease Genes (Nature Biotechnology)

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

Research Highlights

October 22, 2018

Morphogenetic degeneracies in the actomyosin cortex

Sundar Ram Naganathan, S. Fürthauer, Josana Rodriguez, Bruno Thomas Fievet, Frank Jülicher, Julie Ahringer, Carlo Vittorio Cannistraci, Stephan W Grill

One of the great challenges in biology is to understand the mechanisms by which morphogenetic processes arise from molecular activities.…

eLife

October 22, 2018

An integrative tissue-network approach to identify and test human disease genes.

V. Yao, R. Kaletsky, W. Keyes, D. Mor, A. Wong, S. Sohrabi, C. Murphy, O. Troyanskaya

Effective discovery of causal disease genes must overcome the statistical challenges of quantitative genetics studies and the practical limitations of…

Nature Biotechnology

October 16, 2018

Biologically Plausible Online Principal Component Analysis Without Recurrent Neural Dynamics

V. Minden, C. Pehlevan, D. Chklovskii

Artificial neural networks that learn to perform Principal Component Analysis (PCA) and related tasks using strictly local learning rules have…

arXiv:1810.06966

Director

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

Director, CCM; Interim 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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