Einzeltreffer — DigiBib

Gene expression data have played an essential role in many biomedical studies. When the number of genes is large and sample size is limited, there is a 'lack of information' problem, leading to low-quality findings. To tackle this problem, both horizontal and vertical data integrations have been developed, where vertical integration methods collectively analyze data on gene expressions as well as their regulators (such as mutations, DNA methylation and miRNAs). In this article, we conduct a selective review of vertical data integration methods for gene expression data. The reviewed methods cover both marginal and joint analysis and supervised and unsupervised analysis. The main goal is to provide a sketch of the vertical data integration paradigm without digging into too many technical details. We also briefly discuss potential pitfalls, directions for future developments and application notes.

Titel:	Vertical integration methods for gene expression data analysis.
Autor/in / Beteiligte Person:	Wu, M ; Yi, H ; Ma, S
Link:	Full Text Finder (Volltext)
Zeitschrift:	Briefings in bioinformatics, Jg. 22 (2021-05-20), Heft 3
Veröffentlichung:	Oxford : Oxford University Press ; <i>Original Publication</i>: London ; Birmingham, AL : H. Stewart Publications, [2000-, 2021
Medientyp:	academicJournal
ISSN:	1477-4054 (electronic)
DOI:	10.1093/bib/bbaa169
Schlagwort:	Cluster Analysis Data Analysis Humans Unsupervised Machine Learning Gene Expression
Sonstiges:	Nachgewiesen in: MEDLINE Sprachen: English Publication Type: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Review Language: English [Brief Bioinform] 2021 May 20; Vol. 22 (3). MeSH Terms: Gene Expression* ; Cluster Analysis ; Data Analysis ; Humans ; Unsupervised Machine Learning References: PLoS Comput Biol. 2017 Oct 16;13(10):e1005781. (PMID: 29036190) ; High Throughput. 2019 Jan 18;8(1):. (PMID: 30669303) ; BMC Genomics. 2017 Aug 16;18(1):623. (PMID: 28814280) ; IEEE Trans Pattern Anal Mach Intell. 2021 Mar;43(3):798-813. (PMID: 31603770) ; Front Genet. 2018 Aug 23;9:343. (PMID: 30190726) ; J Proteome Res. 2016 Mar 4;15(3):755-65. (PMID: 26653205) ; Transl Cancer Res. 2014 Jun 1;3(3):202-216. (PMID: 25243110) ; Genome Biol. 2017 May 5;18(1):83. (PMID: 28476144) ; Proc Natl Acad Sci U S A. 2018 Jul 24;115(30):7723-7728. (PMID: 29987051) ; BMC Bioinformatics. 2015 Aug 19;16:261. 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Vertical integration methods for gene expression data analysis.