Human microRNAs co-silence in well-separated groups and have different predicted essentialities
Background: Short regulating RNAs guide many cellular processes. Compared with transcription factor proteins they appear to provide more specialized control and their deletions are less frequently lethal. Results: We find large differences between computationally predicted lists of human microRNA (m...
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Veröffentlicht in: | Bioinformatics 2009-04, Vol.25 (8), p.1063-1069 |
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description | Background: Short regulating RNAs guide many cellular processes. Compared with transcription factor proteins they appear to provide more specialized control and their deletions are less frequently lethal. Results: We find large differences between computationally predicted lists of human microRNA (miRNA)–target pairs. Instead of integrating these lists we use the two most accurate of them. Next, we construct the co-regulation network of human miRNAs as nodes by computing the correlation (link weight) between the gene silencing scores of individual miRNAs. In this network, we locate groups of tightly co-regulating nodes (modules). Despite explicitly allowing overlaps the co-regulation modules of miRNAs are well separated. We use the modules and miRNA co-expression data to define and compute miRNA essentiality. Instead of focusing on particular biological functions we identify a miRNA as essential, if it has a low co-expression with the miRNAs in its module. This may be thought of as having many workers performing the same tasks together in one place (non-essential miRNAs) as opposed to a single worker performing those tasks alone (essential miRNA). Conclusions: On the system level, we quantitatively confirm previous findings about the specialized control provided by miRNAs. For knock-out tests we list the groups of our predicted most and least essential miRNAs. In addition, we provide possible explanations for (i) the low number of individually essential miRNAs in Caenorhabdtits elegans and (ii) the high number of ubiquitous miRNAs influencing cell and tissue-specific miRNA expression patterns in mouse and human. Contact: fij@elte.hu Supplementary information: Supplementary data are available at Bioinformatics online. |
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Compared with transcription factor proteins they appear to provide more specialized control and their deletions are less frequently lethal. Results: We find large differences between computationally predicted lists of human microRNA (miRNA)–target pairs. Instead of integrating these lists we use the two most accurate of them. Next, we construct the co-regulation network of human miRNAs as nodes by computing the correlation (link weight) between the gene silencing scores of individual miRNAs. In this network, we locate groups of tightly co-regulating nodes (modules). Despite explicitly allowing overlaps the co-regulation modules of miRNAs are well separated. We use the modules and miRNA co-expression data to define and compute miRNA essentiality. Instead of focusing on particular biological functions we identify a miRNA as essential, if it has a low co-expression with the miRNAs in its module. This may be thought of as having many workers performing the same tasks together in one place (non-essential miRNAs) as opposed to a single worker performing those tasks alone (essential miRNA). Conclusions: On the system level, we quantitatively confirm previous findings about the specialized control provided by miRNAs. For knock-out tests we list the groups of our predicted most and least essential miRNAs. In addition, we provide possible explanations for (i) the low number of individually essential miRNAs in Caenorhabdtits elegans and (ii) the high number of ubiquitous miRNAs influencing cell and tissue-specific miRNA expression patterns in mouse and human. Contact: fij@elte.hu Supplementary information: Supplementary data are available at Bioinformatics online.</description><identifier>ISSN: 1367-4803</identifier><identifier>EISSN: 1460-2059</identifier><identifier>EISSN: 1367-4811</identifier><identifier>DOI: 10.1093/bioinformatics/btp018</identifier><identifier>PMID: 19131366</identifier><identifier>CODEN: BOINFP</identifier><language>eng</language><publisher>Oxford: Oxford University Press</publisher><subject>Animals ; Biological and medical sciences ; Caenorhabditis elegans - genetics ; Computational Biology - methods ; Fundamental and applied biological sciences. Psychology ; General aspects ; Humans ; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) ; Mice ; MicroRNAs - metabolism ; RNA Interference ; Sequence Analysis, RNA</subject><ispartof>Bioinformatics, 2009-04, Vol.25 (8), p.1063-1069</ispartof><rights>The Author 2009. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org 2009</rights><rights>2009 INIST-CNRS</rights><rights>The Author 2009. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c587t-419507eb85b68976138032526375a2b85f62baa13ea772c6be2c871e5fe6c62e3</citedby><cites>FETCH-LOGICAL-c587t-419507eb85b68976138032526375a2b85f62baa13ea772c6be2c871e5fe6c62e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,781,785,1605,27929,27930</link.rule.ids><linktorsrc>$$Uhttps://dx.doi.org/10.1093/bioinformatics/btp018$$EView_record_in_Oxford_University_Press$$FView_record_in_$$GOxford_University_Press</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=21304857$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/19131366$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Boross, Gábor</creatorcontrib><creatorcontrib>Orosz, Katalin</creatorcontrib><creatorcontrib>Farkas, Illés J.</creatorcontrib><title>Human microRNAs co-silence in well-separated groups and have different predicted essentialities</title><title>Bioinformatics</title><addtitle>Bioinformatics</addtitle><description>Background: Short regulating RNAs guide many cellular processes. Compared with transcription factor proteins they appear to provide more specialized control and their deletions are less frequently lethal. Results: We find large differences between computationally predicted lists of human microRNA (miRNA)–target pairs. Instead of integrating these lists we use the two most accurate of them. Next, we construct the co-regulation network of human miRNAs as nodes by computing the correlation (link weight) between the gene silencing scores of individual miRNAs. In this network, we locate groups of tightly co-regulating nodes (modules). Despite explicitly allowing overlaps the co-regulation modules of miRNAs are well separated. We use the modules and miRNA co-expression data to define and compute miRNA essentiality. Instead of focusing on particular biological functions we identify a miRNA as essential, if it has a low co-expression with the miRNAs in its module. This may be thought of as having many workers performing the same tasks together in one place (non-essential miRNAs) as opposed to a single worker performing those tasks alone (essential miRNA). Conclusions: On the system level, we quantitatively confirm previous findings about the specialized control provided by miRNAs. For knock-out tests we list the groups of our predicted most and least essential miRNAs. In addition, we provide possible explanations for (i) the low number of individually essential miRNAs in Caenorhabdtits elegans and (ii) the high number of ubiquitous miRNAs influencing cell and tissue-specific miRNA expression patterns in mouse and human. Contact: fij@elte.hu Supplementary information: Supplementary data are available at Bioinformatics online.</description><subject>Animals</subject><subject>Biological and medical sciences</subject><subject>Caenorhabditis elegans - genetics</subject><subject>Computational Biology - methods</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General aspects</subject><subject>Humans</subject><subject>Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)</subject><subject>Mice</subject><subject>MicroRNAs - metabolism</subject><subject>RNA Interference</subject><subject>Sequence Analysis, RNA</subject><issn>1367-4803</issn><issn>1460-2059</issn><issn>1367-4811</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkc1u1TAQhS0EouXCI4AsJNiF-ie2k2VV0V6kqpVKkRAby3Em4JI4wZNQeHt8latWsCkrW-PvzIzPIeQlZ-84q-VRE8YQuzENbg4ej5p5Yrx6RA55qVkhmKof57vUpigrJg_IM8QbxhQvy_IpOeA1l_lRHxK7XQYX6RB8Gq8ujpH6scDQQ_RAQ6S30PcFwuSSm6GlX9O4TEhdbOk39xNoG7oOEsSZTgna4HcMIOZCcH2YA-Bz8qRzPcKL_bkhn07fX59si_PLsw8nx-eFV5WZi5LXihloKtXoqjaay7y1UEJLo5zI5U6LxjkuwRkjvG5A-MpwUB1orwXIDXm79p3S-GMBnO0Q0OftXYRxQasNF7rOTR8Cd9bxUqkMvv4HvBmXFPMnLK8rbaTMFm6IWqFsH2KCzk4pDC79tpzZXU7275zsmlPWvdo3X5oB2nvVPpgMvNkDDr3ru-SiD3jHCS5ZWSmTObZyOZj_nl2skoAz_LoTufQ9u5T9ttvPX-zpNdcfr4SwWv4BkkTAyA</recordid><startdate>20090415</startdate><enddate>20090415</enddate><creator>Boross, Gábor</creator><creator>Orosz, Katalin</creator><creator>Farkas, Illés J.</creator><general>Oxford University Press</general><general>Oxford Publishing Limited (England)</general><scope>BSCLL</scope><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>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7TM</scope><scope>7TO</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>H94</scope><scope>JG9</scope><scope>JQ2</scope><scope>K9.</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>20090415</creationdate><title>Human microRNAs co-silence in well-separated groups and have different predicted essentialities</title><author>Boross, Gábor ; Orosz, Katalin ; Farkas, Illés J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c587t-419507eb85b68976138032526375a2b85f62baa13ea772c6be2c871e5fe6c62e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Animals</topic><topic>Biological and medical sciences</topic><topic>Caenorhabditis elegans - genetics</topic><topic>Computational Biology - methods</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>General aspects</topic><topic>Humans</topic><topic>Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)</topic><topic>Mice</topic><topic>MicroRNAs - metabolism</topic><topic>RNA Interference</topic><topic>Sequence Analysis, RNA</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Boross, Gábor</creatorcontrib><creatorcontrib>Orosz, Katalin</creatorcontrib><creatorcontrib>Farkas, Illés J.</creatorcontrib><collection>Istex</collection><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>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Bioinformatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Boross, Gábor</au><au>Orosz, Katalin</au><au>Farkas, Illés J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Human microRNAs co-silence in well-separated groups and have different predicted essentialities</atitle><jtitle>Bioinformatics</jtitle><addtitle>Bioinformatics</addtitle><date>2009-04-15</date><risdate>2009</risdate><volume>25</volume><issue>8</issue><spage>1063</spage><epage>1069</epage><pages>1063-1069</pages><issn>1367-4803</issn><eissn>1460-2059</eissn><eissn>1367-4811</eissn><coden>BOINFP</coden><abstract>Background: Short regulating RNAs guide many cellular processes. Compared with transcription factor proteins they appear to provide more specialized control and their deletions are less frequently lethal. Results: We find large differences between computationally predicted lists of human microRNA (miRNA)–target pairs. Instead of integrating these lists we use the two most accurate of them. Next, we construct the co-regulation network of human miRNAs as nodes by computing the correlation (link weight) between the gene silencing scores of individual miRNAs. In this network, we locate groups of tightly co-regulating nodes (modules). Despite explicitly allowing overlaps the co-regulation modules of miRNAs are well separated. We use the modules and miRNA co-expression data to define and compute miRNA essentiality. Instead of focusing on particular biological functions we identify a miRNA as essential, if it has a low co-expression with the miRNAs in its module. This may be thought of as having many workers performing the same tasks together in one place (non-essential miRNAs) as opposed to a single worker performing those tasks alone (essential miRNA). Conclusions: On the system level, we quantitatively confirm previous findings about the specialized control provided by miRNAs. For knock-out tests we list the groups of our predicted most and least essential miRNAs. In addition, we provide possible explanations for (i) the low number of individually essential miRNAs in Caenorhabdtits elegans and (ii) the high number of ubiquitous miRNAs influencing cell and tissue-specific miRNA expression patterns in mouse and human. Contact: fij@elte.hu Supplementary information: Supplementary data are available at Bioinformatics online.</abstract><cop>Oxford</cop><pub>Oxford University Press</pub><pmid>19131366</pmid><doi>10.1093/bioinformatics/btp018</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Animals Biological and medical sciences Caenorhabditis elegans - genetics Computational Biology - methods Fundamental and applied biological sciences. Psychology General aspects Humans Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) Mice MicroRNAs - metabolism RNA Interference Sequence Analysis, RNA |
title | Human microRNAs co-silence in well-separated groups and have different predicted essentialities |
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