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Bioinformatics Software Systems for ...
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Liu, Yu.
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Bioinformatics Software Systems for the Study of Circadian Rhythms.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Bioinformatics Software Systems for the Study of Circadian Rhythms./
Author:
Liu, Yu.
Published:
Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:
140 p.
Notes:
Source: Dissertation Abstracts International, Volume: 80-05(E), Section: B.
Contained By:
Dissertation Abstracts International80-05B(E).
Subject:
Bioinformatics. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10839223
ISBN:
9780438744684
Bioinformatics Software Systems for the Study of Circadian Rhythms.
Liu, Yu.
Bioinformatics Software Systems for the Study of Circadian Rhythms.
- Ann Arbor : ProQuest Dissertations & Theses, 2018 - 140 p.
Source: Dissertation Abstracts International, Volume: 80-05(E), Section: B.
Thesis (Ph.D.)--University of California, Irvine, 2018.
The study of circadian rhythms increasingly relies on high throughput circadian omic data. Processing, annotating and analyzing these data require an efficient and powerful bioinformatics software system. To this end, we have implemented such a system. Major components of this system include genome-wide binding sites predictors, statistical and machine learning pipelines, functional enrichment pipelines, visualization tools and a data management server. Using this system, we have produced high impact publications, a circadian web portal (CircadiOmics, http://circadiomics.ics.uci.edu/), and advanced our understanding of the organization of the circadian transcriptome.
ISBN: 9780438744684Subjects--Topical Terms:
553671
Bioinformatics.
Bioinformatics Software Systems for the Study of Circadian Rhythms.
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The study of circadian rhythms increasingly relies on high throughput circadian omic data. Processing, annotating and analyzing these data require an efficient and powerful bioinformatics software system. To this end, we have implemented such a system. Major components of this system include genome-wide binding sites predictors, statistical and machine learning pipelines, functional enrichment pipelines, visualization tools and a data management server. Using this system, we have produced high impact publications, a circadian web portal (CircadiOmics, http://circadiomics.ics.uci.edu/), and advanced our understanding of the organization of the circadian transcriptome.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10839223
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