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.
Featured News
New research led by Flatiron Institute researchers reveals the source of the mysterious swirling flows in some of nature’s largest cells.
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.
Research Areas
Collaborative Work
Underlying all biological processes are molecules and their interactions with each other. However, our ability to understand how these molecules function over biologically relevant scales remains very limited.
- CCB
- CCM
The Center for Computational Biologyx (CCBx) is an effort by the Center for Computational Biology (CCB) to (a) create and validate quantitative techniques and (b) develop and test theories of biological systems that are predictive of these systems’ behaviors and responses to genetic, chemical and physical perturbations.
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Publication Highlights
Computational tools for cellular scale biophysics Author links open overlay panel
Mathematical models are indispensable for disentangling the interactions through which biological components work together to generate the forces and flows…
Current Opinion in Cell BiologyMinimal motifs for habituating systems
Habituation – a phenomenon in which a dynamical system exhibits a diminishing response to repeated stimulations that eventually recovers when…
ArXivE. coli do not count single molecules
Organisms must perform sensory-motor behaviors to survive. What bounds or constraints limit behavioral performance? Previously, we found that the gradient-climbing…
ArXivDirector
Software
aLENS
This is the simulation tool for tracking assemblies of microtubules driven by motor proteins.
STKFMM
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.
humanbase
Data-driven predictions of gene expression, function, regulation, and interactions in human.
DeepSEA
Deep learning-based algorithmic framework for predicting chromatin effects
FNTM
Functional Networks of Tissues in Mouse
GIANT
Genome-wide Scale functional interaction networks for 144 human tissues and cell types
IMP 2.0
Integrative Multi-species Prediction
KNNimpute
K-Nearest Neighbors Imputation
Nano-Dissection
This server performs in silico nano-dissection, an approach we developed to identify genes with novel cell-lineage specific expression.
SEEK
Search-Based Exploration of Expression Compendium [Human]
SkellySim
SkellySim is a simulation package for simulating cellular components such as flexible filaments, motor proteins, and arbitrary rigid bodies.
Sleipnir
Sleipnir Library for Computational Functional Genomics
URSA(HD)
A data-driven perspective to your gene expression profile for human tissues and diseases.