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Uncovering the statistical physics of 3D chromosomal organization using data-driven modeling
Affiliation:1. Group of Data Modeling, Computational Biology and Predictive Medicine, Institut de Biologie, CNRS/INSERM/PSL Ecole Normale Supérieure, Paris, 75005, France;2. Center for Advanced Imaging, Northwest Building, 52 Oxford St, Suite 147, Harvard University, Cambridge, MA, 02138, USA;3. Department of Chemical Engineering, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA;4. The Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA;1. SUPA, School of Physics and Astronomy, University of Edinburgh, Peter Guthrie Tait Road, Edinburgh, EH9 3FD, UK;2. MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road South, Edinburgh, EH4 2XU, UK
Abstract:In recent years, much effort has been devoted to understanding the three-dimensional (3D) organization of the genome and how genomic structure mediates nuclear function. The development of experimental techniques that combine DNA proximity ligation with high-throughput sequencing, such as Hi-C, have substantially improved our knowledge about chromatin organization. Numerous experimental advancements, not only utilizing DNA proximity ligation but also high-resolution genome imaging (DNA tracing), have required theoretical modeling to determine the structural ensembles consistent with such data. These 3D polymer models of the genome provide an understanding of the physical mechanisms governing genome architecture. Here, we present an overview of the recent advances in modeling the ensemble of 3D chromosomal structures by employing the maximum entropy approach combined with polymer physics. Particularly, we discuss the minimal chromatin model (MiChroM) along with the “maximum entropy genomic annotations from biomarkers associated with structural ensembles” (MEGABASE) model, which have been remarkably successful in the accurate modeling of chromosomes consistent with both Hi-C and DNA-tracing data.
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