Integrated Analysis of Transcriptomic and Proteomic Data

被引:302
作者
Haider, Saad [1 ]
Pal, Ranadip [1 ]
机构
[1] Texas Tech Univ, Dept Elect & Comp Engn, Lubbock, TX 79409 USA
基金
美国国家科学基金会;
关键词
Integrated omics; Data fusion approaches; Transcriptome; Proteome; Joint modeling; Combined analysis review; MESSENGER-RNA EXPRESSION; BRADYRHIZOBIUM-JAPONICUM BACTEROIDS; DESULFOVIBRIO-VULGARIS; PROTEIN ABUNDANCE; MASS-SPECTROMETRY; SACCHAROMYCES-CEREVISIAE; GEL-ELECTROPHORESIS; PREDICT ABUNDANCE; GENE; SEQUENCE;
D O I
10.2174/1389202911314020003
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Until recently, understanding the regulatory behavior of cells has been pursued through independent analysis of the transcriptome or the proteome. Based on the central dogma, it was generally assumed that there exist a direct correspondence between mRNA transcripts and generated protein expressions. However, recent studies have shown that the correlation between mRNA and Protein expressions can be low due to various factors such as different half lives and post transcription machinery. Thus, a joint analysis of the transcriptomic and proteomic data can provide useful insights that may not be deciphered from individual analysis of mRNA or protein expressions. This article reviews the existing major approaches for joint analysis of transcriptomic and proteomic data. We categorize the different approaches into eight main categories based on the initial algorithm and final analysis goal. We further present analogies with other domains and discuss the existing research problems in this area.
引用
收藏
页码:91 / 110
页数:20
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