A personalized pharmaco-epistatic network model of precision medicine
•Functional graph (FunGraph) theory emerges to map pharmacogenetic architecture.•The core tenet of FunGraph is to combine functional mapping and evolutionary game theory into a network framework.•Each agent’s functional roadmap can be visualized and traced from the networks.•FunGraph can map pharmac...
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Veröffentlicht in: | Drug discovery today 2023-07, Vol.28 (7), p.103608-103608, Article 103608 |
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container_title | Drug discovery today |
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creator | Feng, Li Yang, Wuyue Ding, Mengdong Hou, Luke Gragnoli, Claudia Griffin, Christopher Wu, Rongling |
description | •Functional graph (FunGraph) theory emerges to map pharmacogenetic architecture.•The core tenet of FunGraph is to combine functional mapping and evolutionary game theory into a network framework.•Each agent’s functional roadmap can be visualized and traced from the networks.•FunGraph can map pharmacogenetics networks for each and every subject.•FunGraph can quantify interindividual and context-specific differences in network architecture.
Precision medicine, the utilization of targeted treatments to address an individual’s disease, relies on knowledge about the genetic cause of that individual’s drug response. Here, we present a functional graph (FunGraph) theory to chart comprehensive pharmacogenetic architecture for each and every patient. FunGraph is the combination of functional mapping – a dynamic model for genetic mapping and evolutionary game theory guiding interactive strategies. It coalesces all pharmacogenetic factors into multilayer and multiplex networks that fully capture bidirectional, signed and weighted epistasis. It can visualize and interrogate how epistasis moves in the cell and how this movement leads to patient- and context-specific genetic architecture in response to organismic physiology. We discuss the future implementation of FunGraph to achieve precision medicine. |
doi_str_mv | 10.1016/j.drudis.2023.103608 |
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Precision medicine, the utilization of targeted treatments to address an individual’s disease, relies on knowledge about the genetic cause of that individual’s drug response. Here, we present a functional graph (FunGraph) theory to chart comprehensive pharmacogenetic architecture for each and every patient. FunGraph is the combination of functional mapping – a dynamic model for genetic mapping and evolutionary game theory guiding interactive strategies. It coalesces all pharmacogenetic factors into multilayer and multiplex networks that fully capture bidirectional, signed and weighted epistasis. It can visualize and interrogate how epistasis moves in the cell and how this movement leads to patient- and context-specific genetic architecture in response to organismic physiology. We discuss the future implementation of FunGraph to achieve precision medicine.</description><identifier>ISSN: 1359-6446</identifier><identifier>EISSN: 1878-5832</identifier><identifier>DOI: 10.1016/j.drudis.2023.103608</identifier><identifier>PMID: 37149282</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>association studies ; Epistasis ; functional graph theory ; functional mapping ; genetic network ; personalized medicine</subject><ispartof>Drug discovery today, 2023-07, Vol.28 (7), p.103608-103608, Article 103608</ispartof><rights>2023 Elsevier Ltd</rights><rights>Copyright © 2023 Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c362t-ed50005375a515978eeffa95bcfb2dafdc72472e21312e522c280d5393d3ddbd3</citedby><cites>FETCH-LOGICAL-c362t-ed50005375a515978eeffa95bcfb2dafdc72472e21312e522c280d5393d3ddbd3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.drudis.2023.103608$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37149282$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Feng, Li</creatorcontrib><creatorcontrib>Yang, Wuyue</creatorcontrib><creatorcontrib>Ding, Mengdong</creatorcontrib><creatorcontrib>Hou, Luke</creatorcontrib><creatorcontrib>Gragnoli, Claudia</creatorcontrib><creatorcontrib>Griffin, Christopher</creatorcontrib><creatorcontrib>Wu, Rongling</creatorcontrib><title>A personalized pharmaco-epistatic network model of precision medicine</title><title>Drug discovery today</title><addtitle>Drug Discov Today</addtitle><description>•Functional graph (FunGraph) theory emerges to map pharmacogenetic architecture.•The core tenet of FunGraph is to combine functional mapping and evolutionary game theory into a network framework.•Each agent’s functional roadmap can be visualized and traced from the networks.•FunGraph can map pharmacogenetics networks for each and every subject.•FunGraph can quantify interindividual and context-specific differences in network architecture.
Precision medicine, the utilization of targeted treatments to address an individual’s disease, relies on knowledge about the genetic cause of that individual’s drug response. Here, we present a functional graph (FunGraph) theory to chart comprehensive pharmacogenetic architecture for each and every patient. FunGraph is the combination of functional mapping – a dynamic model for genetic mapping and evolutionary game theory guiding interactive strategies. It coalesces all pharmacogenetic factors into multilayer and multiplex networks that fully capture bidirectional, signed and weighted epistasis. It can visualize and interrogate how epistasis moves in the cell and how this movement leads to patient- and context-specific genetic architecture in response to organismic physiology. We discuss the future implementation of FunGraph to achieve precision medicine.</description><subject>association studies</subject><subject>Epistasis</subject><subject>functional graph theory</subject><subject>functional mapping</subject><subject>genetic network</subject><subject>personalized medicine</subject><issn>1359-6446</issn><issn>1878-5832</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kEtPwzAQhC0EoqXwDxDKkUuKvY7zuCBVVXlIlbjA2XLtjXBJ4mCnIPj1uErhyGlXq5kdzUfIJaNzRll-s50bvzM2zIECjyee0_KITFlZlKkoORzHnYsqzbMsn5CzELaUMqhEfkomvGBZBSVMyWqR9OiD61Rjv9Ek_avyrdIuxd6GQQ1WJx0On86_Ja0z2CSuTnqP2gbruqRFY7Xt8Jyc1KoJeHGYM_Jyt3pePqTrp_vH5WKdap7DkKIRlFLBC6EEE1VRIta1qsRG1xswqja6gKwABMYZoADQUFIjeMUNN2Zj-Ixcj3977953GAbZ2qCxaVSHbhcklIxWwHKeR2k2SrV3IXisZe9tq_yXZFTuAcqtHAHKPUA5Aoy2q0PCbhPb_Zl-iUXB7SjA2PPDopdBW-x0JBGxDNI4-3_CD6jsg9Y</recordid><startdate>202307</startdate><enddate>202307</enddate><creator>Feng, Li</creator><creator>Yang, Wuyue</creator><creator>Ding, Mengdong</creator><creator>Hou, Luke</creator><creator>Gragnoli, Claudia</creator><creator>Griffin, Christopher</creator><creator>Wu, Rongling</creator><general>Elsevier Ltd</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>202307</creationdate><title>A personalized pharmaco-epistatic network model of precision medicine</title><author>Feng, Li ; Yang, Wuyue ; Ding, Mengdong ; Hou, Luke ; Gragnoli, Claudia ; Griffin, Christopher ; Wu, Rongling</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c362t-ed50005375a515978eeffa95bcfb2dafdc72472e21312e522c280d5393d3ddbd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>association studies</topic><topic>Epistasis</topic><topic>functional graph theory</topic><topic>functional mapping</topic><topic>genetic network</topic><topic>personalized medicine</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Feng, Li</creatorcontrib><creatorcontrib>Yang, Wuyue</creatorcontrib><creatorcontrib>Ding, Mengdong</creatorcontrib><creatorcontrib>Hou, Luke</creatorcontrib><creatorcontrib>Gragnoli, Claudia</creatorcontrib><creatorcontrib>Griffin, Christopher</creatorcontrib><creatorcontrib>Wu, Rongling</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Drug discovery today</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Feng, Li</au><au>Yang, Wuyue</au><au>Ding, Mengdong</au><au>Hou, Luke</au><au>Gragnoli, Claudia</au><au>Griffin, Christopher</au><au>Wu, Rongling</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A personalized pharmaco-epistatic network model of precision medicine</atitle><jtitle>Drug discovery today</jtitle><addtitle>Drug Discov Today</addtitle><date>2023-07</date><risdate>2023</risdate><volume>28</volume><issue>7</issue><spage>103608</spage><epage>103608</epage><pages>103608-103608</pages><artnum>103608</artnum><issn>1359-6446</issn><eissn>1878-5832</eissn><abstract>•Functional graph (FunGraph) theory emerges to map pharmacogenetic architecture.•The core tenet of FunGraph is to combine functional mapping and evolutionary game theory into a network framework.•Each agent’s functional roadmap can be visualized and traced from the networks.•FunGraph can map pharmacogenetics networks for each and every subject.•FunGraph can quantify interindividual and context-specific differences in network architecture.
Precision medicine, the utilization of targeted treatments to address an individual’s disease, relies on knowledge about the genetic cause of that individual’s drug response. Here, we present a functional graph (FunGraph) theory to chart comprehensive pharmacogenetic architecture for each and every patient. FunGraph is the combination of functional mapping – a dynamic model for genetic mapping and evolutionary game theory guiding interactive strategies. It coalesces all pharmacogenetic factors into multilayer and multiplex networks that fully capture bidirectional, signed and weighted epistasis. It can visualize and interrogate how epistasis moves in the cell and how this movement leads to patient- and context-specific genetic architecture in response to organismic physiology. We discuss the future implementation of FunGraph to achieve precision medicine.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>37149282</pmid><doi>10.1016/j.drudis.2023.103608</doi><tpages>1</tpages></addata></record> |
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subjects | association studies Epistasis functional graph theory functional mapping genetic network personalized medicine |
title | A personalized pharmaco-epistatic network model of precision medicine |
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