Comprehensive review of the identification of essential genes using computational methods: focusing on feature implementation and assessment. (29th November 2018)
- Record Type:
- Journal Article
- Title:
- Comprehensive review of the identification of essential genes using computational methods: focusing on feature implementation and assessment. (29th November 2018)
- Main Title:
- Comprehensive review of the identification of essential genes using computational methods: focusing on feature implementation and assessment
- Authors:
- Dong, Chuan
Jin, Yan-Ting
Hua, Hong-Li
Wen, Qing-Feng
Luo, Sen
Zheng, Wen-Xin
Guo, Feng-Biao - Abstract:
- Abstract: Essential genes have attracted increasing attention in recent years due to the important functions of these genes in organisms. Among the methods used to identify the essential genes, accurate and efficient computational methods can make up for the deficiencies of expensive and time-consuming experimental technologies. In this review, we have collected researches on essential gene predictions in prokaryotes and eukaryotes and summarized the five predominant types of features used in these studies. The five types of features include evolutionary conservation, domain information, network topology, sequence component and expression level. We have described how to implement the useful forms of these features and evaluated their performance based on the data of Escherichia coli MG1655, Bacillus subtilis 168 and human. The prerequisite and applicable range of these features is described. In addition, we have investigated the techniques used to weight features in various models. To facilitate researchers in the field, two available online tools, which are accessible for free and can be directly used to predict gene essentiality in prokaryotes and humans, were referred. This article provides a simple guide for the identification of essential genes in prokaryotes and eukaryotes.
- Is Part Of:
- Briefings in bioinformatics. Volume 21:Number 1(2020)
- Journal:
- Briefings in bioinformatics
- Issue:
- Volume 21:Number 1(2020)
- Issue Display:
- Volume 21, Issue 1 (2020)
- Year:
- 2020
- Volume:
- 21
- Issue:
- 1
- Issue Sort Value:
- 2020-0021-0001-0000
- Page Start:
- 171
- Page End:
- 181
- Publication Date:
- 2018-11-29
- Subjects:
- essential genes -- computational methods -- feature assessment -- online tool
Genetics -- Data processing -- Periodicals
Molecular biology -- Data processing -- Periodicals
Genomes -- Data processing -- Periodicals
572.80285 - Journal URLs:
- http://bib.oxfordjournals.org ↗
http://www.oxfordjournals.org/content?genre=journal&issn=1477-4054 ↗
http://ukcatalogue.oup.com/ ↗
http://firstsearch.oclc.org ↗ - DOI:
- 10.1093/bib/bby116 ↗
- Languages:
- English
- ISSNs:
- 1467-5463
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 2283.958363
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 12783.xml