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김동혁

Kim, Donghyuk
Systems Biology and Machine Learning Lab.
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dc.citation.endPage 104 -
dc.citation.startPage 99 -
dc.citation.title COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL -
dc.citation.volume 21 -
dc.contributor.author Bang, Ina -
dc.contributor.author Nong, Linh Khanh -
dc.contributor.author Park, Joon Young -
dc.contributor.author Le, Hoa Thi -
dc.contributor.author Lee, Sang-Mok -
dc.contributor.author Kim, Donghyuk -
dc.date.accessioned 2023-12-21T13:08:53Z -
dc.date.available 2023-12-21T13:08:53Z -
dc.date.created 2023-01-27 -
dc.date.issued 2023-01 -
dc.description.abstract Genome-scale studies of the bacterial regulatory network have been leveraged by declining sequencing cost and advances in ChIP (chromatin immunoprecipitation) methods. Of which, ChIP-exo has proven competent with its near-single base-pair resolution. While several algorithms and programs have been developed for different analytical steps in ChIP-exo data processing, there is a lack of effort in incorporat-ing them into a convenient bioinformatics pipeline that is intuitive and publicly available. In this paper, we developed ChIP-exo Analysis Pipeline (ChEAP) that executes the one-step process, starting from trim-ming and aligning raw sequencing reads to visualization of ChIP-exo results. The pipeline was imple-mented on the interactive web-based Python development environment - Jupyter Notebook, which is compatible with the Google Colab cloud platform to facilitate the sharing of codes and collaboration among researchers. Additionally, users could exploit the free GPU and CPU resources allocated by Colab to carry out computing tasks regardless of the performance of their local machines. The utility of ChEAP was demonstrated with the ChIP-exo datasets of RpoN sigma factor in E. coli K-12 MG1655. To analyze two raw data files, ChEAP runtime was 2 min and 25 s. Subsequent analyses identified 113 RpoN binding sites showing a conserved RpoN binding pattern in the motif search. ChEAP application in ChIP-exo data analysis is extensive and flexible for the parallel processing of data from various organisms. (c) 2022 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. -
dc.identifier.bibliographicCitation COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL, v.21, pp.99 - 104 -
dc.identifier.doi 10.1016/j.csbj.2022.11.053 -
dc.identifier.issn 2001-0370 -
dc.identifier.scopusid 2-s2.0-85144023120 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/62033 -
dc.identifier.wosid 000904436800010 -
dc.language 영어 -
dc.publisher ELSEVIER -
dc.title ChEAP: ChIP-exo analysis pipeline and the investigation of Escherichia coli RpoN protein-DNA interactions -
dc.type Article -
dc.description.isOpenAccess TRUE -
dc.relation.journalWebOfScienceCategory Biochemistry & Molecular Biology; Biotechnology & Applied Microbiology -
dc.relation.journalResearchArea Biochemistry & Molecular Biology; Biotechnology & Applied Microbiology -
dc.type.docType Article -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordAuthor ChIP-exo -
dc.subject.keywordAuthor Analysis pipeline -
dc.subject.keywordAuthor RpoN -
dc.subject.keywordAuthor Sigmulon -
dc.subject.keywordAuthor Sigma factor -
dc.subject.keywordAuthor Escherichia coli -
dc.subject.keywordPlus NITROGEN ASSIMILATION -
dc.subject.keywordPlus REGULON -
dc.subject.keywordPlus SIGMA(54) -
dc.subject.keywordPlus DATABASE -

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