Using Markov chains of nucleotide sequences as a possible precursor to predict functional roles of human genome: a case study on inactive chromatin regions
- 주제(키워드) Chromatin maps , Nucleotide frequency patterns , Markov chain , Noncoding DNA , Computational epigenetics
- 관리정보기술 faculty
- 등재 SCIE, SCOPUS
- 발행기관 FUNPEC-EDITORA
- 발행년도 2016
- 총서유형 Journal
- URI http://www.dcollection.net/handler/ewha/000000140096
- 본문언어 영어
- Published As http://dx.doi.org/10.4238/gmr.15039004
초록/요약
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.
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