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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| Published in | Current genomics Vol. 14; no. 2; pp. 91 - 110 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
United Arab Emirates
Bentham Science Publishers Ltd
01.04.2013
Bentham Science Publishers |
| Subjects | |
| Online Access | Get full text |
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| 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. |
|---|---|
| AbstractList | 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. 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. 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.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. |
| Author | Ranadip Pal Saad Haider |
| AuthorAffiliation | Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX, 79409, USA |
| AuthorAffiliation_xml | – name: Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX, 79409, USA |
| Author_xml | – sequence: 1 givenname: Saad surname: Haider fullname: Haider, Saad – sequence: 2 givenname: Ranadip surname: Pal fullname: Pal, Ranadip |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/24082820$$D View this record in MEDLINE/PubMed |
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| Publisher | Bentham Science Publishers Ltd Bentham Science Publishers |
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| Snippet | Until recently, understanding the regulatory behavior of cells has been pursued through independent analysis of
the transcriptome or the proteome. Based on the... Until recently, understanding the regulatory behavior of cells has been pursued through independent analysis of the transcriptome or the proteome. Based on the... |
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| StartPage | 91 |
| Title | Integrated Analysis of Transcriptomic and Proteomic Data |
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