Information-theoretic sensitivity analysis: a general method for credit assignment in complex networks
Most systems can be represented as networks that couple a series of nodes to each other via one or more edges, with typically unknown equations governing their quantitative behaviour. A major question then pertains to the importance of each of the elements that act as system inputs in determining th...
Gespeichert in:
| Veröffentlicht in: | Journal of the Royal Society interface 2008-02, Vol.5 (19), p.223-235 |
|---|---|
| Hauptverfasser: | , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 235 |
|---|---|
| container_issue | 19 |
| container_start_page | 223 |
| container_title | Journal of the Royal Society interface |
| container_volume | 5 |
| creator | Lüdtke, Niklas Panzeri, Stefano Brown, Martin Broomhead, David S Knowles, Joshua Montemurro, Marcelo A Kell, Douglas B |
| description | Most systems can be represented as networks that couple a series of nodes to each other via one or more edges, with typically unknown equations governing their quantitative behaviour. A major question then pertains to the importance of each of the elements that act as system inputs in determining the output(s). We show that any such system can be treated as a 'communication channel' for which the associations between inputs and outputs can be quantified via a decomposition of their mutual information into different components characterizing the main effect of individual inputs and their interactions. Unlike variance-based approaches, our novel methodology can easily accommodate correlated inputs. |
| doi_str_mv | 10.1098/rsif.2007.1079 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_istex</sourceid><recordid>TN_cdi_proquest_miscellaneous_70099992</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>70099992</sourcerecordid><originalsourceid>FETCH-LOGICAL-c631t-8418c5bd44a8cdc564f17be175f098921761832dc941ee8acf9c808280c51143</originalsourceid><addsrcrecordid>eNp9UU1v1DAQjRCIlsKVI_KJWxZ_5MMBCQkVCkWVEKjiwGXkdca7bhN7a3vb5t_jVVYLPYAv9sjvvXkzryheMrpgtJNvQrRmwSltc9l2j4pj1la8rJuGPz68ZXdUPIvxilLRirp-Whyxtu6qrmHHhTl3xodRJetdmdboAyarSUQXbbK3Nk1EOTVM0ca3RJEVOgxqICOmte9JphIdsLeJqBjtyo3oErGOaD9uBrwnDtOdD9fxefHEqCHii_19Ulyefbo8_VJefPt8fvrhotSNYKmUFZO6XvZVpaTudd1UhrVLzHZNHrbjrG2YFLzXXcUQpdKm05JKLqmuGavESfF-lt1slyP2OrvJbmET7KjCBF5ZePjj7BpW_ha4kE3dsCzwei8Q_M0WY4LRRo3DoBz6bYSW0i4fnoGLGaiDjzGgOTRhFHbJwC4Z2CUDu2Qy4dXf1v7A91FkgJgBwU95RV5bTBNc-W3I-4__li1nlo0J7w-qKlxD04q2hp-ygh_fxddflfwIZxnPZ_zartZ3NiA8aJcL6xIGozRCDawDzkUmvfsvaWdJ-8xz6UACsx3y5nsjfgNtS9b_</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>70099992</pqid></control><display><type>article</type><title>Information-theoretic sensitivity analysis: a general method for credit assignment in complex networks</title><source>MEDLINE</source><source>PubMed Central</source><creator>Lüdtke, Niklas ; Panzeri, Stefano ; Brown, Martin ; Broomhead, David S ; Knowles, Joshua ; Montemurro, Marcelo A ; Kell, Douglas B</creator><creatorcontrib>Lüdtke, Niklas ; Panzeri, Stefano ; Brown, Martin ; Broomhead, David S ; Knowles, Joshua ; Montemurro, Marcelo A ; Kell, Douglas B</creatorcontrib><description>Most systems can be represented as networks that couple a series of nodes to each other via one or more edges, with typically unknown equations governing their quantitative behaviour. A major question then pertains to the importance of each of the elements that act as system inputs in determining the output(s). We show that any such system can be treated as a 'communication channel' for which the associations between inputs and outputs can be quantified via a decomposition of their mutual information into different components characterizing the main effect of individual inputs and their interactions. Unlike variance-based approaches, our novel methodology can easily accommodate correlated inputs.</description><identifier>ISSN: 1742-5689</identifier><identifier>EISSN: 1742-5662</identifier><identifier>DOI: 10.1098/rsif.2007.1079</identifier><identifier>PMID: 17594961</identifier><language>eng</language><publisher>London: The Royal Society</publisher><subject>Communication Channel ; Computer Simulation ; Entropy ; Information Theory ; Models, Biological ; Monte Carlo Method ; Mutual Information ; NF-kappa B - metabolism ; NFκB ; Research Article ; Sensitivity Analysis ; Sensitivity and Specificity ; Signal Transduction ; Systems Biology - methods</subject><ispartof>Journal of the Royal Society interface, 2008-02, Vol.5 (19), p.223-235</ispartof><rights>Copyright © 2007 The Royal Society</rights><rights>Copyright © 2007 The Royal Society 2007</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c631t-8418c5bd44a8cdc564f17be175f098921761832dc941ee8acf9c808280c51143</citedby><cites>FETCH-LOGICAL-c631t-8418c5bd44a8cdc564f17be175f098921761832dc941ee8acf9c808280c51143</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2386561/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2386561/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/17594961$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lüdtke, Niklas</creatorcontrib><creatorcontrib>Panzeri, Stefano</creatorcontrib><creatorcontrib>Brown, Martin</creatorcontrib><creatorcontrib>Broomhead, David S</creatorcontrib><creatorcontrib>Knowles, Joshua</creatorcontrib><creatorcontrib>Montemurro, Marcelo A</creatorcontrib><creatorcontrib>Kell, Douglas B</creatorcontrib><title>Information-theoretic sensitivity analysis: a general method for credit assignment in complex networks</title><title>Journal of the Royal Society interface</title><addtitle>J R Soc Interface</addtitle><description>Most systems can be represented as networks that couple a series of nodes to each other via one or more edges, with typically unknown equations governing their quantitative behaviour. A major question then pertains to the importance of each of the elements that act as system inputs in determining the output(s). We show that any such system can be treated as a 'communication channel' for which the associations between inputs and outputs can be quantified via a decomposition of their mutual information into different components characterizing the main effect of individual inputs and their interactions. Unlike variance-based approaches, our novel methodology can easily accommodate correlated inputs.</description><subject>Communication Channel</subject><subject>Computer Simulation</subject><subject>Entropy</subject><subject>Information Theory</subject><subject>Models, Biological</subject><subject>Monte Carlo Method</subject><subject>Mutual Information</subject><subject>NF-kappa B - metabolism</subject><subject>NFκB</subject><subject>Research Article</subject><subject>Sensitivity Analysis</subject><subject>Sensitivity and Specificity</subject><subject>Signal Transduction</subject><subject>Systems Biology - methods</subject><issn>1742-5689</issn><issn>1742-5662</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9UU1v1DAQjRCIlsKVI_KJWxZ_5MMBCQkVCkWVEKjiwGXkdca7bhN7a3vb5t_jVVYLPYAv9sjvvXkzryheMrpgtJNvQrRmwSltc9l2j4pj1la8rJuGPz68ZXdUPIvxilLRirp-Whyxtu6qrmHHhTl3xodRJetdmdboAyarSUQXbbK3Nk1EOTVM0ca3RJEVOgxqICOmte9JphIdsLeJqBjtyo3oErGOaD9uBrwnDtOdD9fxefHEqCHii_19Ulyefbo8_VJefPt8fvrhotSNYKmUFZO6XvZVpaTudd1UhrVLzHZNHrbjrG2YFLzXXcUQpdKm05JKLqmuGavESfF-lt1slyP2OrvJbmET7KjCBF5ZePjj7BpW_ha4kE3dsCzwei8Q_M0WY4LRRo3DoBz6bYSW0i4fnoGLGaiDjzGgOTRhFHbJwC4Z2CUDu2Qy4dXf1v7A91FkgJgBwU95RV5bTBNc-W3I-4__li1nlo0J7w-qKlxD04q2hp-ygh_fxddflfwIZxnPZ_zartZ3NiA8aJcL6xIGozRCDawDzkUmvfsvaWdJ-8xz6UACsx3y5nsjfgNtS9b_</recordid><startdate>20080206</startdate><enddate>20080206</enddate><creator>Lüdtke, Niklas</creator><creator>Panzeri, Stefano</creator><creator>Brown, Martin</creator><creator>Broomhead, David S</creator><creator>Knowles, Joshua</creator><creator>Montemurro, Marcelo A</creator><creator>Kell, Douglas B</creator><general>The Royal Society</general><scope>BSCLL</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>7X8</scope><scope>5PM</scope></search><sort><creationdate>20080206</creationdate><title>Information-theoretic sensitivity analysis: a general method for credit assignment in complex networks</title><author>Lüdtke, Niklas ; Panzeri, Stefano ; Brown, Martin ; Broomhead, David S ; Knowles, Joshua ; Montemurro, Marcelo A ; Kell, Douglas B</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c631t-8418c5bd44a8cdc564f17be175f098921761832dc941ee8acf9c808280c51143</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Communication Channel</topic><topic>Computer Simulation</topic><topic>Entropy</topic><topic>Information Theory</topic><topic>Models, Biological</topic><topic>Monte Carlo Method</topic><topic>Mutual Information</topic><topic>NF-kappa B - metabolism</topic><topic>NFκB</topic><topic>Research Article</topic><topic>Sensitivity Analysis</topic><topic>Sensitivity and Specificity</topic><topic>Signal Transduction</topic><topic>Systems Biology - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lüdtke, Niklas</creatorcontrib><creatorcontrib>Panzeri, Stefano</creatorcontrib><creatorcontrib>Brown, Martin</creatorcontrib><creatorcontrib>Broomhead, David S</creatorcontrib><creatorcontrib>Knowles, Joshua</creatorcontrib><creatorcontrib>Montemurro, Marcelo A</creatorcontrib><creatorcontrib>Kell, Douglas B</creatorcontrib><collection>Istex</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of the Royal Society interface</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lüdtke, Niklas</au><au>Panzeri, Stefano</au><au>Brown, Martin</au><au>Broomhead, David S</au><au>Knowles, Joshua</au><au>Montemurro, Marcelo A</au><au>Kell, Douglas B</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Information-theoretic sensitivity analysis: a general method for credit assignment in complex networks</atitle><jtitle>Journal of the Royal Society interface</jtitle><addtitle>J R Soc Interface</addtitle><date>2008-02-06</date><risdate>2008</risdate><volume>5</volume><issue>19</issue><spage>223</spage><epage>235</epage><pages>223-235</pages><issn>1742-5689</issn><eissn>1742-5662</eissn><abstract>Most systems can be represented as networks that couple a series of nodes to each other via one or more edges, with typically unknown equations governing their quantitative behaviour. A major question then pertains to the importance of each of the elements that act as system inputs in determining the output(s). We show that any such system can be treated as a 'communication channel' for which the associations between inputs and outputs can be quantified via a decomposition of their mutual information into different components characterizing the main effect of individual inputs and their interactions. Unlike variance-based approaches, our novel methodology can easily accommodate correlated inputs.</abstract><cop>London</cop><pub>The Royal Society</pub><pmid>17594961</pmid><doi>10.1098/rsif.2007.1079</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1742-5689 |
| ispartof | Journal of the Royal Society interface, 2008-02, Vol.5 (19), p.223-235 |
| issn | 1742-5689 1742-5662 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_70099992 |
| source | MEDLINE; PubMed Central |
| subjects | Communication Channel Computer Simulation Entropy Information Theory Models, Biological Monte Carlo Method Mutual Information NF-kappa B - metabolism NFκB Research Article Sensitivity Analysis Sensitivity and Specificity Signal Transduction Systems Biology - methods |
| title | Information-theoretic sensitivity analysis: a general method for credit assignment in complex networks |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-28T10%3A50%3A47IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_istex&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Information-theoretic%20sensitivity%20analysis:%20a%20general%20method%20for%20credit%20assignment%20in%20complex%20networks&rft.jtitle=Journal%20of%20the%20Royal%20Society%20interface&rft.au=L%C3%BCdtke,%20Niklas&rft.date=2008-02-06&rft.volume=5&rft.issue=19&rft.spage=223&rft.epage=235&rft.pages=223-235&rft.issn=1742-5689&rft.eissn=1742-5662&rft_id=info:doi/10.1098/rsif.2007.1079&rft_dat=%3Cproquest_istex%3E70099992%3C/proquest_istex%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=70099992&rft_id=info:pmid/17594961&rfr_iscdi=true |