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dc.contributor.author원정임-
dc.date.accessioned2021-03-09T01:20:31Z-
dc.date.available2021-03-09T01:20:31Z-
dc.date.issued2019-06-
dc.identifier.citationBIOMED RESEARCH INTERNATIONAL, v. 2019, article no. 4767354en_US
dc.identifier.issn2314-6133-
dc.identifier.issn2314-6141-
dc.identifier.urihttps://www.hindawi.com/journals/bmri/2019/4767354/-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/160279-
dc.description.abstractGenomic analysis begins with de novo assembly of short-read fragments in order to reconstruct full-length base sequences without exploiting a reference genome sequence. Then, in the annotation step, gene locations are identified within the base sequences, and the structures and functions of these genes are determined. Recently, a wide range of powerful tools have been developed and published for whole-genome analysis, enabling even individual researchers in small laboratories to perform whole-genome analyses on their objects of interest. However, these analytical tools are generally complex and use diverse algorithms, parameter setting methods, and input formats; thus, it remains difficult for individual researchers to select, utilize, and combine these tools to obtain their final results. To resolve these issues, we have developed a genome analysis pipeline (GAAP) for semiautomated, iterative, and high-throughput analysis of whole-genome data. This pipeline is designed to perform read correction, de novo genome (transcriptome) assembly, gene prediction, and functional annotation using a range of proven tools and databases. We aim to assist non-IT researchers by describing each stage of analysis in detail and discussing current approaches. We also provide practical advice on how to access and use the bioinformatics tools and databases and how to implement the provided suggestions. Whole-genome analysis of Toxocara canis is used as case study to show intermediate results at each stage, demonstrating the practicality of the proposed method.en_US
dc.description.sponsorshipTis research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (no.2017R1D1A1B03030969) and by Hallym University Research Fund (HRF-201610-011). Tis work was also supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (no. 2017R1A2B4007831).en_US
dc.language.isoenen_US
dc.publisherHINDAWI LTDen_US
dc.titleGAAP: A Genome Assembly+Annotation Pipelineen_US
dc.typeArticleen_US
dc.identifier.doi10.1155/2019/4767354-
dc.relation.journalBIOMED RESEARCH INTERNATIONAL-
dc.contributor.googleauthorKong, Jinhwa-
dc.contributor.googleauthorHuh, Sun-
dc.contributor.googleauthorWon, Jung-Im-
dc.contributor.googleauthorYoon, Jeehee-
dc.contributor.googleauthorKim, Baeksop-
dc.contributor.googleauthorKim, Kiyong-
dc.relation.code2019038599-
dc.sector.campusS-
dc.sector.daehakCOLLEGE OF ENGINEERING[S]-
dc.sector.departmentCENTER FOR INNOVATION IN ENGINEERING EDUCATION-
dc.identifier.pidjiwon-
dc.identifier.orcidhttps://orcid.org/0000-0003-3591-7735-
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COLLEGE OF ENGINEERING[S](공과대학) > ETC
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