Systems Biology Approaches for Understanding Genome Architecture
The linear and three-dimensional arrangement and composition of chromatin in eukaryotic genomes underlies the mechanisms directing gene regulation. Understanding this organization requires the integration of many data types and experimental results. Here we describe the approach of integrating genome-wide protein–DNA binding data to determine chromatin states. To investigate spatial aspects of genome organization, we present a detailed description of how to run stochastic simulations of protein movements within a simulated nucleus in 3D. This systems level approach enables the development of novel questions aimed at understanding the basic mechanisms that regulate genome dynamics.
Key wordsGenome organization Systems biology Stochastic spatial simulations Hidden Markov models Chromatin states
We would like to thank Guillaume Filion for providing the HMMt package and for advice on using it, Jeremy Bancroft for work on the implementation of HMMt to work with ChIP-chip data, and Hugo Schmidt and Zsuzsanna Sükösd Etches for their Smoldyn models of the nucleus. We thank Steve Andrews for development and continued support of Smoldyn, some of the cited code snippets, and many fruitful discussions over the years.
SS was supported by the Biotechnology and Biological Sciences Research Council UK grant BBS/E/B/000C0405; KL was supported by a Royal Society University Research Fellowship and a Microsoft Research Faculty Fellowship.
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