Abstract
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.
Keywords: Integrated omics, Data fusion approaches, Transcriptome, Proteome, Joint modeling, Combined analysis review
Current Genomics
Title:Integrated Analysis of Transcriptomic and Proteomic Data
Volume: 14 Issue: 2
Author(s): Saad Haider and Ranadip Pal
Affiliation:
Keywords: Integrated omics, Data fusion approaches, Transcriptome, Proteome, Joint modeling, Combined analysis review
Abstract: 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.
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Cite this article as:
Haider Saad and Pal Ranadip, Integrated Analysis of Transcriptomic and Proteomic Data, Current Genomics 2013; 14 (2) . https://dx.doi.org/10.2174/1389202911314020003
DOI https://dx.doi.org/10.2174/1389202911314020003 |
Print ISSN 1389-2029 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5488 |
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