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Integrated Analysis of Transcriptomic and Proteomic Data

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....

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Detalles Bibliográficos
Autores principales: Haider, Saad, Pal, Ranadip
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bentham Science Publishers 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3637682/
https://www.ncbi.nlm.nih.gov/pubmed/24082820
http://dx.doi.org/10.2174/1389202911314020003
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author Haider, Saad
Pal, Ranadip
author_facet Haider, Saad
Pal, Ranadip
author_sort Haider, Saad
collection PubMed
description 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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spelling pubmed-36376822013-10-01 Integrated Analysis of Transcriptomic and Proteomic Data Haider, Saad Pal, Ranadip Curr Genomics Article 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. Bentham Science Publishers 2013-04 2013-04 /pmc/articles/PMC3637682/ /pubmed/24082820 http://dx.doi.org/10.2174/1389202911314020003 Text en ©2013 Bentham Science Publishers http://creativecommons.org/licenses/by/2.5/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.5/), which permits unrestrictive use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Article
Haider, Saad
Pal, Ranadip
Integrated Analysis of Transcriptomic and Proteomic Data
title Integrated Analysis of Transcriptomic and Proteomic Data
title_full Integrated Analysis of Transcriptomic and Proteomic Data
title_fullStr Integrated Analysis of Transcriptomic and Proteomic Data
title_full_unstemmed Integrated Analysis of Transcriptomic and Proteomic Data
title_short Integrated Analysis of Transcriptomic and Proteomic Data
title_sort integrated analysis of transcriptomic and proteomic data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3637682/
https://www.ncbi.nlm.nih.gov/pubmed/24082820
http://dx.doi.org/10.2174/1389202911314020003
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