Abstract
Recent advances in computational epigenetics have provided new opportunities to evaluate n-gram probabilistic language models. In this paper, we describe a systematic genome-wide approach for predicting functional roles in inactive chromatin regions by using a sequence-based Markovian chromatin map of the human genome. We demonstrate that Markov chains of sequences can be used as a precursor to predict functional roles in heterochromatin regions and provide an example comparing two publicly available chromatin annotations of large-scale epigenomics projects: ENCODE project consortium and Roadmap Epigenomics consortium.
Original language | English |
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Article number | 15039004 |
Journal | Genetics and Molecular Research |
Volume | 15 |
Issue number | 3 |
DOIs | |
State | Published - 30 Aug 2016 |
Bibliographical note
Publisher Copyright:© 2016 The Authors.
Keywords
- Chromatin maps
- Computational epigenetics
- Markov chain
- Noncoding DNA
- Nucleotide frequency patterns