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Integrating multiple 'omics' analysis for microbial biology: application and methodologies
1 Center for Ecogenomics, Biodesign Institute, Arizona State University, Tempe, AZ 85287-6501, USA 2 Division of Biometrics II, Office of Biometrics/OTS/CDER/FDA, Silver Spring, MD 20993-0002, USA 3 Division of Biometrics IV, Office of Biometrics/OTS/CDER/FDA, Silver Spring, MD 20993-0002, USA Recen...
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Published in: | Microbiology (Society for General Microbiology) 2010-02, Vol.156 (2), p.287-301 |
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description | 1 Center for Ecogenomics, Biodesign Institute, Arizona State University, Tempe, AZ 85287-6501, USA
2 Division of Biometrics II, Office of Biometrics/OTS/CDER/FDA, Silver Spring, MD 20993-0002, USA
3 Division of Biometrics IV, Office of Biometrics/OTS/CDER/FDA, Silver Spring, MD 20993-0002, USA
Recent advances in various omics technologies enable quantitative monitoring of the abundance of various biological molecules in a high-throughput manner, and thus allow determination of their variation between different biological states on a genomic scale. Several popular omics platforms that have been used in microbial systems biology include transcriptomics, which measures mRNA transcript levels; proteomics, which quantifies protein abundance; metabolomics, which determines abundance of small cellular metabolites; interactomics, which resolves the whole set of molecular interactions in cells; and fluxomics, which establishes dynamic changes of molecules within a cell over time. However, no single omics analysis can fully unravel the complexities of fundamental microbial biology. Therefore, integration of multiple layers of information, the multi-omics approach, is required to acquire a precise picture of living micro-organisms. In spite of this being a challenging task, some attempts have been made recently to integrate heterogeneous omics datasets in various microbial systems and the results have demonstrated that the multi-omics approach is a powerful tool for understanding the functional principles and dynamics of total cellular systems. This article reviews some basic concepts of various experimental omics approaches, recent application of the integrated omics for exploring metabolic and regulatory mechanisms in microbes, and advances in computational and statistical methodologies associated with integrated omics analyses. Online databases and bioinformatic infrastructure available for integrated omics analyses are also briefly discussed.
Correspondence Weiwen Zhang Weiwen.Zhang{at}asu.edu |
doi_str_mv | 10.1099/mic.0.034793-0 |
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2 Division of Biometrics II, Office of Biometrics/OTS/CDER/FDA, Silver Spring, MD 20993-0002, USA
3 Division of Biometrics IV, Office of Biometrics/OTS/CDER/FDA, Silver Spring, MD 20993-0002, USA
Recent advances in various omics technologies enable quantitative monitoring of the abundance of various biological molecules in a high-throughput manner, and thus allow determination of their variation between different biological states on a genomic scale. Several popular omics platforms that have been used in microbial systems biology include transcriptomics, which measures mRNA transcript levels; proteomics, which quantifies protein abundance; metabolomics, which determines abundance of small cellular metabolites; interactomics, which resolves the whole set of molecular interactions in cells; and fluxomics, which establishes dynamic changes of molecules within a cell over time. However, no single omics analysis can fully unravel the complexities of fundamental microbial biology. Therefore, integration of multiple layers of information, the multi-omics approach, is required to acquire a precise picture of living micro-organisms. In spite of this being a challenging task, some attempts have been made recently to integrate heterogeneous omics datasets in various microbial systems and the results have demonstrated that the multi-omics approach is a powerful tool for understanding the functional principles and dynamics of total cellular systems. This article reviews some basic concepts of various experimental omics approaches, recent application of the integrated omics for exploring metabolic and regulatory mechanisms in microbes, and advances in computational and statistical methodologies associated with integrated omics analyses. Online databases and bioinformatic infrastructure available for integrated omics analyses are also briefly discussed.
Correspondence Weiwen Zhang Weiwen.Zhang{at}asu.edu</description><identifier>ISSN: 1350-0872</identifier><identifier>EISSN: 1465-2080</identifier><identifier>DOI: 10.1099/mic.0.034793-0</identifier><identifier>PMID: 19910409</identifier><language>eng</language><publisher>Reading: Soc General Microbiol</publisher><subject>Animals ; Biological and medical sciences ; Computational Biology - methods ; Databases, Factual ; Fundamental and applied biological sciences. Psychology ; General aspects ; Genomics - methods ; Humans ; Metabolomics ; Microbiology ; Proteomics - methods ; Software</subject><ispartof>Microbiology (Society for General Microbiology), 2010-02, Vol.156 (2), p.287-301</ispartof><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c494t-859c3b6d286b56f0f3e39063efb738c0cefe89b6debcce92f6addf39c07610d03</citedby><cites>FETCH-LOGICAL-c494t-859c3b6d286b56f0f3e39063efb738c0cefe89b6debcce92f6addf39c07610d03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=22394141$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/19910409$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhang, Weiwen</creatorcontrib><creatorcontrib>Li, Feng</creatorcontrib><creatorcontrib>Nie, Lei</creatorcontrib><title>Integrating multiple 'omics' analysis for microbial biology: application and methodologies</title><title>Microbiology (Society for General Microbiology)</title><addtitle>Microbiology</addtitle><description>1 Center for Ecogenomics, Biodesign Institute, Arizona State University, Tempe, AZ 85287-6501, USA
2 Division of Biometrics II, Office of Biometrics/OTS/CDER/FDA, Silver Spring, MD 20993-0002, USA
3 Division of Biometrics IV, Office of Biometrics/OTS/CDER/FDA, Silver Spring, MD 20993-0002, USA
Recent advances in various omics technologies enable quantitative monitoring of the abundance of various biological molecules in a high-throughput manner, and thus allow determination of their variation between different biological states on a genomic scale. Several popular omics platforms that have been used in microbial systems biology include transcriptomics, which measures mRNA transcript levels; proteomics, which quantifies protein abundance; metabolomics, which determines abundance of small cellular metabolites; interactomics, which resolves the whole set of molecular interactions in cells; and fluxomics, which establishes dynamic changes of molecules within a cell over time. However, no single omics analysis can fully unravel the complexities of fundamental microbial biology. Therefore, integration of multiple layers of information, the multi-omics approach, is required to acquire a precise picture of living micro-organisms. In spite of this being a challenging task, some attempts have been made recently to integrate heterogeneous omics datasets in various microbial systems and the results have demonstrated that the multi-omics approach is a powerful tool for understanding the functional principles and dynamics of total cellular systems. This article reviews some basic concepts of various experimental omics approaches, recent application of the integrated omics for exploring metabolic and regulatory mechanisms in microbes, and advances in computational and statistical methodologies associated with integrated omics analyses. Online databases and bioinformatic infrastructure available for integrated omics analyses are also briefly discussed.
Correspondence Weiwen Zhang Weiwen.Zhang{at}asu.edu</description><subject>Animals</subject><subject>Biological and medical sciences</subject><subject>Computational Biology - methods</subject><subject>Databases, Factual</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General aspects</subject><subject>Genomics - methods</subject><subject>Humans</subject><subject>Metabolomics</subject><subject>Microbiology</subject><subject>Proteomics - methods</subject><subject>Software</subject><issn>1350-0872</issn><issn>1465-2080</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><recordid>eNp90DFv1DAUB3ALgWhpWRlRFnosOZ7txInZUEVLpUossHSxHOc5Z-TEwc4J3bevT4lgY7Ll93vP9p-QdxT2FKT8NDqzhz3wqpG8hBfkklaiLhm08DLveQ0ltA27IG9S-gWQi0BfkwsqJYUK5CV5epgWHKJe3DQU49EvbvZY7EKem3aFnrQ_JZcKG2KRj2LonPZF54IPw-lzoefZO5Obw5RtX4y4HEJ_LjpM1-SV1T7h2229Ij_vvv64_VY-fr9_uP3yWJpKVkvZ1tLwTvSsFV0tLFiOXILgaLuGtwYMWmxlBtgZg5JZofvecmmgERR64Fdkt86dY_h9xLSo0SWD3usJwzGphvNW8qoWWd78VzLKQa5wv8L845QiWjVHN-p4UhTUOffcaBSoNXd1fsP7bfKxG7H_x7egM_iwAZ2M9jbqybj01zHGZUUrmt3H1R3ccPjjIqoBpy35cL6V1kIxxdqGPwMiP5rh</recordid><startdate>20100201</startdate><enddate>20100201</enddate><creator>Zhang, Weiwen</creator><creator>Li, Feng</creator><creator>Nie, Lei</creator><general>Soc General Microbiol</general><general>Society for General Microbiology</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7T7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>20100201</creationdate><title>Integrating multiple 'omics' analysis for microbial biology: application and methodologies</title><author>Zhang, Weiwen ; Li, Feng ; Nie, Lei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c494t-859c3b6d286b56f0f3e39063efb738c0cefe89b6debcce92f6addf39c07610d03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Animals</topic><topic>Biological and medical sciences</topic><topic>Computational Biology - methods</topic><topic>Databases, Factual</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>General aspects</topic><topic>Genomics - methods</topic><topic>Humans</topic><topic>Metabolomics</topic><topic>Microbiology</topic><topic>Proteomics - methods</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Weiwen</creatorcontrib><creatorcontrib>Li, Feng</creatorcontrib><creatorcontrib>Nie, Lei</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Microbiology (Society for General Microbiology)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Weiwen</au><au>Li, Feng</au><au>Nie, Lei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Integrating multiple 'omics' analysis for microbial biology: application and methodologies</atitle><jtitle>Microbiology (Society for General Microbiology)</jtitle><addtitle>Microbiology</addtitle><date>2010-02-01</date><risdate>2010</risdate><volume>156</volume><issue>2</issue><spage>287</spage><epage>301</epage><pages>287-301</pages><issn>1350-0872</issn><eissn>1465-2080</eissn><abstract>1 Center for Ecogenomics, Biodesign Institute, Arizona State University, Tempe, AZ 85287-6501, USA
2 Division of Biometrics II, Office of Biometrics/OTS/CDER/FDA, Silver Spring, MD 20993-0002, USA
3 Division of Biometrics IV, Office of Biometrics/OTS/CDER/FDA, Silver Spring, MD 20993-0002, USA
Recent advances in various omics technologies enable quantitative monitoring of the abundance of various biological molecules in a high-throughput manner, and thus allow determination of their variation between different biological states on a genomic scale. Several popular omics platforms that have been used in microbial systems biology include transcriptomics, which measures mRNA transcript levels; proteomics, which quantifies protein abundance; metabolomics, which determines abundance of small cellular metabolites; interactomics, which resolves the whole set of molecular interactions in cells; and fluxomics, which establishes dynamic changes of molecules within a cell over time. However, no single omics analysis can fully unravel the complexities of fundamental microbial biology. Therefore, integration of multiple layers of information, the multi-omics approach, is required to acquire a precise picture of living micro-organisms. In spite of this being a challenging task, some attempts have been made recently to integrate heterogeneous omics datasets in various microbial systems and the results have demonstrated that the multi-omics approach is a powerful tool for understanding the functional principles and dynamics of total cellular systems. This article reviews some basic concepts of various experimental omics approaches, recent application of the integrated omics for exploring metabolic and regulatory mechanisms in microbes, and advances in computational and statistical methodologies associated with integrated omics analyses. Online databases and bioinformatic infrastructure available for integrated omics analyses are also briefly discussed.
Correspondence Weiwen Zhang Weiwen.Zhang{at}asu.edu</abstract><cop>Reading</cop><pub>Soc General Microbiol</pub><pmid>19910409</pmid><doi>10.1099/mic.0.034793-0</doi><tpages>15</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Animals Biological and medical sciences Computational Biology - methods Databases, Factual Fundamental and applied biological sciences. Psychology General aspects Genomics - methods Humans Metabolomics Microbiology Proteomics - methods Software |
title | Integrating multiple 'omics' analysis for microbial biology: application and methodologies |
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