Back to Search
Start Over
Bridging the resolution gap in structural modeling of 3D genome organization
- Source :
- PLoS Computational Biology, Vol 7, Iss 7, p e1002125 (2011), PLoS Computational Biology, PLoS
- Publication Year :
- 2011
- Publisher :
- Public Library of Science (PLoS), 2011.
-
Abstract
- Over the last decade, and especially after the advent of fluorescent in situ hybridization imaging and chromosome conformation capture methods, the availability of experimental data on genome three-dimensional organization has dramatically increased. We now have access to unprecedented details of how genomes organize within the interphase nucleus. Development of new computational approaches to leverage this data has already resulted in the first three-dimensional structures of genomic domains and genomes. Such approaches expand our knowledge of the chromatin folding principles, which has been classically studied using polymer physics and molecular simulations. Our outlook describes computational approaches for integrating experimental data with polymer physics, thereby bridging the resolution gap for structural determination of genomes and genomic domains.<br />Spain. Ministerio de Ciencia e InnovacioĢn (BFU2010-19310)<br />National Cancer Institute (U.S.)<br />David H. Koch Institute for Integrative Cancer Research at MIT
- Subjects :
- Models, Molecular
Macromolecular Assemblies
Bridging (networking)
Biophysics
Genomics
Computational biology
Review
Biology
Genome
Biophysics Simulations
Chromosomes
Structural genomics
Chromosome conformation capture
Cellular and Molecular Neuroscience
Genetics
Humans
Molecular Biology
lcsh:QH301-705.5
Ecology, Evolution, Behavior and Systematics
Genomic organization
Ecology
Models, Genetic
Chromosome Biology
Computational Biology
Chromatin
Computational Theory and Mathematics
lcsh:Biology (General)
Modeling and Simulation
Polymer physics
Structural Genomics
Subjects
Details
- Language :
- English
- ISSN :
- 15537358
- Volume :
- 7
- Issue :
- 7
- Database :
- OpenAIRE
- Journal :
- PLoS Computational Biology
- Accession number :
- edsair.doi.dedup.....d799c277283ec49f82160f624402312a