A theory of optimal differential gene expression
We investigate a model of optimal regulation, intended to describe large-scale differential gene expression. Relations between the optimal expression patterns and the function of genes are deduced from an optimality principle: the regulators have to maximise a fitness function which they influence d...
Gespeichert in:
| Veröffentlicht in: | BioSystems 2004-08, Vol.76 (1), p.261-278 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 278 |
|---|---|
| container_issue | 1 |
| container_start_page | 261 |
| container_title | BioSystems |
| container_volume | 76 |
| creator | Liebermeister, Wolfram Klipp, Edda Schuster, Stefan Heinrich, Reinhart |
| description | We investigate a model of optimal regulation, intended to describe large-scale differential gene expression. Relations between the optimal expression patterns and the function of genes are deduced from an optimality principle: the regulators have to maximise a fitness function which they influence directly via a cost term, and indirectly via their control on important cell variables, such as metabolic fluxes. According to the model, the optimal linear response to small perturbations reflects the regulators’ functions, namely their linear influences on the cell variables. The optimal behaviour can be realised by a linear feedback mechanism. Known or assumed properties of response coefficients lead to predictions about regulation patterns. A symmetry relation predicted for deletion experiments is verified with gene expression data. Where the optimality assumption is valid, our results justify the use of expression data for functional annotation and for pathway reconstruction and suggest the use of linear factor models for the analysis of gene expression data. |
| doi_str_mv | 10.1016/j.biosystems.2004.05.022 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_66847025</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0303264704000863</els_id><sourcerecordid>66847025</sourcerecordid><originalsourceid>FETCH-LOGICAL-c370t-4b7bf1a0fa40eb9cff87e62501f223a7e0a924495c86966f39462b6e045f1ea03</originalsourceid><addsrcrecordid>eNqFkM1OwzAQhC0EoqXwCignbglrx3aSY6n4kypxgbOVOGtwlcTBThF9e1y1Uo_sZbXSzI7mIyShkFGg8n6TNdaFXZiwDxkD4BmIDBg7I3NaFiwtc8bPyRxyyFMmeTEjVyFsII4o6SWZUZELSnk1J7BMpi90fpc4k7hxsn3dJa01Bj0Ok43HJw6Y4O_oMQTrhmtyYeou4M1xL8jH0-P76iVdvz2_rpbrVOcFTClvisbQGkzNAZtKG1MWKJkAahjL6wKhrhjnldClrKQ0ecUlayQCF4ZiDfmC3B3-jt59bzFMqrdBY9fVA7ptUFKWvAAmorA8CLV3IXg0avSxhd8pCmpPS23UiZba01IgVKQVrbfHjG3TY3syHvFEwcNBgLHpj0WvgrY4aGytRz2p1tn_U_4AnGKAKg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>66847025</pqid></control><display><type>article</type><title>A theory of optimal differential gene expression</title><source>MEDLINE</source><source>Elsevier ScienceDirect Journals Complete</source><creator>Liebermeister, Wolfram ; Klipp, Edda ; Schuster, Stefan ; Heinrich, Reinhart</creator><creatorcontrib>Liebermeister, Wolfram ; Klipp, Edda ; Schuster, Stefan ; Heinrich, Reinhart</creatorcontrib><description>We investigate a model of optimal regulation, intended to describe large-scale differential gene expression. Relations between the optimal expression patterns and the function of genes are deduced from an optimality principle: the regulators have to maximise a fitness function which they influence directly via a cost term, and indirectly via their control on important cell variables, such as metabolic fluxes. According to the model, the optimal linear response to small perturbations reflects the regulators’ functions, namely their linear influences on the cell variables. The optimal behaviour can be realised by a linear feedback mechanism. Known or assumed properties of response coefficients lead to predictions about regulation patterns. A symmetry relation predicted for deletion experiments is verified with gene expression data. Where the optimality assumption is valid, our results justify the use of expression data for functional annotation and for pathway reconstruction and suggest the use of linear factor models for the analysis of gene expression data.</description><identifier>ISSN: 0303-2647</identifier><identifier>EISSN: 1872-8324</identifier><identifier>DOI: 10.1016/j.biosystems.2004.05.022</identifier><identifier>PMID: 15351149</identifier><language>eng</language><publisher>Ireland: Elsevier Ireland Ltd</publisher><subject>Adaptation, Physiological - physiology ; Animals ; Cell Physiological Phenomena ; Feedback - physiology ; Gene expression ; Gene Expression Regulation - physiology ; Gene function ; Genes, Regulator - genetics ; Genetic regulation ; Humans ; Linear model ; Metabolic control analysis ; Models, Genetic ; Multienzyme Complexes - metabolism ; Optimality principle ; Signal Transduction - physiology ; Transcription Factors - metabolism</subject><ispartof>BioSystems, 2004-08, Vol.76 (1), p.261-278</ispartof><rights>2004 Elsevier Ireland Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c370t-4b7bf1a0fa40eb9cff87e62501f223a7e0a924495c86966f39462b6e045f1ea03</citedby><cites>FETCH-LOGICAL-c370t-4b7bf1a0fa40eb9cff87e62501f223a7e0a924495c86966f39462b6e045f1ea03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.biosystems.2004.05.022$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3548,27923,27924,45994</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/15351149$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Liebermeister, Wolfram</creatorcontrib><creatorcontrib>Klipp, Edda</creatorcontrib><creatorcontrib>Schuster, Stefan</creatorcontrib><creatorcontrib>Heinrich, Reinhart</creatorcontrib><title>A theory of optimal differential gene expression</title><title>BioSystems</title><addtitle>Biosystems</addtitle><description>We investigate a model of optimal regulation, intended to describe large-scale differential gene expression. Relations between the optimal expression patterns and the function of genes are deduced from an optimality principle: the regulators have to maximise a fitness function which they influence directly via a cost term, and indirectly via their control on important cell variables, such as metabolic fluxes. According to the model, the optimal linear response to small perturbations reflects the regulators’ functions, namely their linear influences on the cell variables. The optimal behaviour can be realised by a linear feedback mechanism. Known or assumed properties of response coefficients lead to predictions about regulation patterns. A symmetry relation predicted for deletion experiments is verified with gene expression data. Where the optimality assumption is valid, our results justify the use of expression data for functional annotation and for pathway reconstruction and suggest the use of linear factor models for the analysis of gene expression data.</description><subject>Adaptation, Physiological - physiology</subject><subject>Animals</subject><subject>Cell Physiological Phenomena</subject><subject>Feedback - physiology</subject><subject>Gene expression</subject><subject>Gene Expression Regulation - physiology</subject><subject>Gene function</subject><subject>Genes, Regulator - genetics</subject><subject>Genetic regulation</subject><subject>Humans</subject><subject>Linear model</subject><subject>Metabolic control analysis</subject><subject>Models, Genetic</subject><subject>Multienzyme Complexes - metabolism</subject><subject>Optimality principle</subject><subject>Signal Transduction - physiology</subject><subject>Transcription Factors - metabolism</subject><issn>0303-2647</issn><issn>1872-8324</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkM1OwzAQhC0EoqXwCignbglrx3aSY6n4kypxgbOVOGtwlcTBThF9e1y1Uo_sZbXSzI7mIyShkFGg8n6TNdaFXZiwDxkD4BmIDBg7I3NaFiwtc8bPyRxyyFMmeTEjVyFsII4o6SWZUZELSnk1J7BMpi90fpc4k7hxsn3dJa01Bj0Ok43HJw6Y4O_oMQTrhmtyYeou4M1xL8jH0-P76iVdvz2_rpbrVOcFTClvisbQGkzNAZtKG1MWKJkAahjL6wKhrhjnldClrKQ0ecUlayQCF4ZiDfmC3B3-jt59bzFMqrdBY9fVA7ptUFKWvAAmorA8CLV3IXg0avSxhd8pCmpPS23UiZba01IgVKQVrbfHjG3TY3syHvFEwcNBgLHpj0WvgrY4aGytRz2p1tn_U_4AnGKAKg</recordid><startdate>20040801</startdate><enddate>20040801</enddate><creator>Liebermeister, Wolfram</creator><creator>Klipp, Edda</creator><creator>Schuster, Stefan</creator><creator>Heinrich, Reinhart</creator><general>Elsevier Ireland Ltd</general><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></search><sort><creationdate>20040801</creationdate><title>A theory of optimal differential gene expression</title><author>Liebermeister, Wolfram ; Klipp, Edda ; Schuster, Stefan ; Heinrich, Reinhart</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c370t-4b7bf1a0fa40eb9cff87e62501f223a7e0a924495c86966f39462b6e045f1ea03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Adaptation, Physiological - physiology</topic><topic>Animals</topic><topic>Cell Physiological Phenomena</topic><topic>Feedback - physiology</topic><topic>Gene expression</topic><topic>Gene Expression Regulation - physiology</topic><topic>Gene function</topic><topic>Genes, Regulator - genetics</topic><topic>Genetic regulation</topic><topic>Humans</topic><topic>Linear model</topic><topic>Metabolic control analysis</topic><topic>Models, Genetic</topic><topic>Multienzyme Complexes - metabolism</topic><topic>Optimality principle</topic><topic>Signal Transduction - physiology</topic><topic>Transcription Factors - metabolism</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liebermeister, Wolfram</creatorcontrib><creatorcontrib>Klipp, Edda</creatorcontrib><creatorcontrib>Schuster, Stefan</creatorcontrib><creatorcontrib>Heinrich, Reinhart</creatorcontrib><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><jtitle>BioSystems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liebermeister, Wolfram</au><au>Klipp, Edda</au><au>Schuster, Stefan</au><au>Heinrich, Reinhart</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A theory of optimal differential gene expression</atitle><jtitle>BioSystems</jtitle><addtitle>Biosystems</addtitle><date>2004-08-01</date><risdate>2004</risdate><volume>76</volume><issue>1</issue><spage>261</spage><epage>278</epage><pages>261-278</pages><issn>0303-2647</issn><eissn>1872-8324</eissn><abstract>We investigate a model of optimal regulation, intended to describe large-scale differential gene expression. Relations between the optimal expression patterns and the function of genes are deduced from an optimality principle: the regulators have to maximise a fitness function which they influence directly via a cost term, and indirectly via their control on important cell variables, such as metabolic fluxes. According to the model, the optimal linear response to small perturbations reflects the regulators’ functions, namely their linear influences on the cell variables. The optimal behaviour can be realised by a linear feedback mechanism. Known or assumed properties of response coefficients lead to predictions about regulation patterns. A symmetry relation predicted for deletion experiments is verified with gene expression data. Where the optimality assumption is valid, our results justify the use of expression data for functional annotation and for pathway reconstruction and suggest the use of linear factor models for the analysis of gene expression data.</abstract><cop>Ireland</cop><pub>Elsevier Ireland Ltd</pub><pmid>15351149</pmid><doi>10.1016/j.biosystems.2004.05.022</doi><tpages>18</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0303-2647 |
| ispartof | BioSystems, 2004-08, Vol.76 (1), p.261-278 |
| issn | 0303-2647 1872-8324 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_66847025 |
| source | MEDLINE; Elsevier ScienceDirect Journals Complete |
| subjects | Adaptation, Physiological - physiology Animals Cell Physiological Phenomena Feedback - physiology Gene expression Gene Expression Regulation - physiology Gene function Genes, Regulator - genetics Genetic regulation Humans Linear model Metabolic control analysis Models, Genetic Multienzyme Complexes - metabolism Optimality principle Signal Transduction - physiology Transcription Factors - metabolism |
| title | A theory of optimal differential gene expression |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-10T19%3A41%3A54IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20theory%20of%20optimal%20differential%20gene%20expression&rft.jtitle=BioSystems&rft.au=Liebermeister,%20Wolfram&rft.date=2004-08-01&rft.volume=76&rft.issue=1&rft.spage=261&rft.epage=278&rft.pages=261-278&rft.issn=0303-2647&rft.eissn=1872-8324&rft_id=info:doi/10.1016/j.biosystems.2004.05.022&rft_dat=%3Cproquest_cross%3E66847025%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=66847025&rft_id=info:pmid/15351149&rft_els_id=S0303264704000863&rfr_iscdi=true |