An ontology-driven method for hierarchical mining of temporal patterns: application to HIV drug resistance research
Many biomedical research databases contain time-oriented data resulting from longitudinal, time-series and time-dependent study designs, knowledge of which is not handled explicitly by most data-analytic methods. To make use of such knowledge about research data, we have developed an ontology-driven...
Gespeichert in:
Veröffentlicht in: | AMIA ... Annual Symposium proceedings 2007-10, Vol.2007, p.614-619 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 619 |
---|---|
container_issue | |
container_start_page | 614 |
container_title | AMIA ... Annual Symposium proceedings |
container_volume | 2007 |
creator | Raj, Rashmi O'Connor, Martin J Das, Amar K |
description | Many biomedical research databases contain time-oriented data resulting from longitudinal, time-series and time-dependent study designs, knowledge of which is not handled explicitly by most data-analytic methods. To make use of such knowledge about research data, we have developed an ontology-driven temporal mining method, called ChronoMiner. Most mining algorithms require data be inputted in a single table. ChronoMiner, in contrast, can search for interesting temporal patterns among multiple input tables and at different levels of hierarchical representation. In this paper, we present the application of our method to the discovery of temporal associations between newly arising mutations in the HIV genome and past drug regimens. We discuss the various components of ChronoMiner, including its user interface, and provide results of a study indicating the efficiency and potential value of ChronoMiner on an existing HIV drug resistance data repository. |
format | Article |
fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_2655843</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>70142667</sourcerecordid><originalsourceid>FETCH-LOGICAL-p179t-5cb0a4665b22df14fb8f6374b8b7472619031e51a5792700a4532680f1c642c13</originalsourceid><addsrcrecordid>eNpVkE1LxDAQhosg7rr6FyQnb4UkzUfrQVgWPxYWvKjXkqbTNtImNUkX9t_bxVX0NMPMw_MOc5YsCedFyrAUi-QyhA-MmeS5uEgWJBdFVuBimYS1Rc5G17v2kNbe7MGiAWLnatQ4jzoDXnndGa16NBhrbItcgyIMo_PzaFQxgrfhDqlx7GcqGmdRdOh5-45qP7XIQzAhKqvh2MJRdpWcN6oPcH2qq-Tt8eF185zuXp62m_UuHYksYsp1hRUTgleU1g1hTZU3IpOsyivJJBWkwBkBThSXBZV4ZnlGRY4bogWjmmSr5P7bO07VALUGG-eby9GbQflD6ZQp_2-s6crW7UsqOM9ZNgtuTwLvPicIsRxM0ND3yoKbQikxYVQIOYM3f5N-I37-nH0B_6R7Aw</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>70142667</pqid></control><display><type>article</type><title>An ontology-driven method for hierarchical mining of temporal patterns: application to HIV drug resistance research</title><source>MEDLINE</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><creator>Raj, Rashmi ; O'Connor, Martin J ; Das, Amar K</creator><creatorcontrib>Raj, Rashmi ; O'Connor, Martin J ; Das, Amar K</creatorcontrib><description>Many biomedical research databases contain time-oriented data resulting from longitudinal, time-series and time-dependent study designs, knowledge of which is not handled explicitly by most data-analytic methods. To make use of such knowledge about research data, we have developed an ontology-driven temporal mining method, called ChronoMiner. Most mining algorithms require data be inputted in a single table. ChronoMiner, in contrast, can search for interesting temporal patterns among multiple input tables and at different levels of hierarchical representation. In this paper, we present the application of our method to the discovery of temporal associations between newly arising mutations in the HIV genome and past drug regimens. We discuss the various components of ChronoMiner, including its user interface, and provide results of a study indicating the efficiency and potential value of ChronoMiner on an existing HIV drug resistance data repository.</description><identifier>EISSN: 1559-4076</identifier><identifier>PMID: 18693909</identifier><language>eng</language><publisher>United States: American Medical Informatics Association</publisher><subject>Algorithms ; Anti-HIV Agents - therapeutic use ; Databases as Topic ; Drug Resistance, Viral - genetics ; Genome, Viral ; HIV - genetics ; HIV Infections - drug therapy ; HIV Infections - virology ; Humans ; Information Storage and Retrieval - methods ; Knowledge Bases ; Longitudinal Studies ; Mutation ; Time ; User-Computer Interface ; Viral Load ; Vocabulary, Controlled</subject><ispartof>AMIA ... Annual Symposium proceedings, 2007-10, Vol.2007, p.614-619</ispartof><rights>2007 AMIA - All rights reserved. 2007</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2655843/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2655843/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,727,780,784,885,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/18693909$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Raj, Rashmi</creatorcontrib><creatorcontrib>O'Connor, Martin J</creatorcontrib><creatorcontrib>Das, Amar K</creatorcontrib><title>An ontology-driven method for hierarchical mining of temporal patterns: application to HIV drug resistance research</title><title>AMIA ... Annual Symposium proceedings</title><addtitle>AMIA Annu Symp Proc</addtitle><description>Many biomedical research databases contain time-oriented data resulting from longitudinal, time-series and time-dependent study designs, knowledge of which is not handled explicitly by most data-analytic methods. To make use of such knowledge about research data, we have developed an ontology-driven temporal mining method, called ChronoMiner. Most mining algorithms require data be inputted in a single table. ChronoMiner, in contrast, can search for interesting temporal patterns among multiple input tables and at different levels of hierarchical representation. In this paper, we present the application of our method to the discovery of temporal associations between newly arising mutations in the HIV genome and past drug regimens. We discuss the various components of ChronoMiner, including its user interface, and provide results of a study indicating the efficiency and potential value of ChronoMiner on an existing HIV drug resistance data repository.</description><subject>Algorithms</subject><subject>Anti-HIV Agents - therapeutic use</subject><subject>Databases as Topic</subject><subject>Drug Resistance, Viral - genetics</subject><subject>Genome, Viral</subject><subject>HIV - genetics</subject><subject>HIV Infections - drug therapy</subject><subject>HIV Infections - virology</subject><subject>Humans</subject><subject>Information Storage and Retrieval - methods</subject><subject>Knowledge Bases</subject><subject>Longitudinal Studies</subject><subject>Mutation</subject><subject>Time</subject><subject>User-Computer Interface</subject><subject>Viral Load</subject><subject>Vocabulary, Controlled</subject><issn>1559-4076</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpVkE1LxDAQhosg7rr6FyQnb4UkzUfrQVgWPxYWvKjXkqbTNtImNUkX9t_bxVX0NMPMw_MOc5YsCedFyrAUi-QyhA-MmeS5uEgWJBdFVuBimYS1Rc5G17v2kNbe7MGiAWLnatQ4jzoDXnndGa16NBhrbItcgyIMo_PzaFQxgrfhDqlx7GcqGmdRdOh5-45qP7XIQzAhKqvh2MJRdpWcN6oPcH2qq-Tt8eF185zuXp62m_UuHYksYsp1hRUTgleU1g1hTZU3IpOsyivJJBWkwBkBThSXBZV4ZnlGRY4bogWjmmSr5P7bO07VALUGG-eby9GbQflD6ZQp_2-s6crW7UsqOM9ZNgtuTwLvPicIsRxM0ND3yoKbQikxYVQIOYM3f5N-I37-nH0B_6R7Aw</recordid><startdate>20071011</startdate><enddate>20071011</enddate><creator>Raj, Rashmi</creator><creator>O'Connor, Martin J</creator><creator>Das, Amar K</creator><general>American Medical Informatics Association</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20071011</creationdate><title>An ontology-driven method for hierarchical mining of temporal patterns: application to HIV drug resistance research</title><author>Raj, Rashmi ; O'Connor, Martin J ; Das, Amar K</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p179t-5cb0a4665b22df14fb8f6374b8b7472619031e51a5792700a4532680f1c642c13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Algorithms</topic><topic>Anti-HIV Agents - therapeutic use</topic><topic>Databases as Topic</topic><topic>Drug Resistance, Viral - genetics</topic><topic>Genome, Viral</topic><topic>HIV - genetics</topic><topic>HIV Infections - drug therapy</topic><topic>HIV Infections - virology</topic><topic>Humans</topic><topic>Information Storage and Retrieval - methods</topic><topic>Knowledge Bases</topic><topic>Longitudinal Studies</topic><topic>Mutation</topic><topic>Time</topic><topic>User-Computer Interface</topic><topic>Viral Load</topic><topic>Vocabulary, Controlled</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Raj, Rashmi</creatorcontrib><creatorcontrib>O'Connor, Martin J</creatorcontrib><creatorcontrib>Das, Amar K</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>AMIA ... Annual Symposium proceedings</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Raj, Rashmi</au><au>O'Connor, Martin J</au><au>Das, Amar K</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An ontology-driven method for hierarchical mining of temporal patterns: application to HIV drug resistance research</atitle><jtitle>AMIA ... Annual Symposium proceedings</jtitle><addtitle>AMIA Annu Symp Proc</addtitle><date>2007-10-11</date><risdate>2007</risdate><volume>2007</volume><spage>614</spage><epage>619</epage><pages>614-619</pages><eissn>1559-4076</eissn><abstract>Many biomedical research databases contain time-oriented data resulting from longitudinal, time-series and time-dependent study designs, knowledge of which is not handled explicitly by most data-analytic methods. To make use of such knowledge about research data, we have developed an ontology-driven temporal mining method, called ChronoMiner. Most mining algorithms require data be inputted in a single table. ChronoMiner, in contrast, can search for interesting temporal patterns among multiple input tables and at different levels of hierarchical representation. In this paper, we present the application of our method to the discovery of temporal associations between newly arising mutations in the HIV genome and past drug regimens. We discuss the various components of ChronoMiner, including its user interface, and provide results of a study indicating the efficiency and potential value of ChronoMiner on an existing HIV drug resistance data repository.</abstract><cop>United States</cop><pub>American Medical Informatics Association</pub><pmid>18693909</pmid><tpages>6</tpages></addata></record> |
fulltext | fulltext |
identifier | EISSN: 1559-4076 |
ispartof | AMIA ... Annual Symposium proceedings, 2007-10, Vol.2007, p.614-619 |
issn | 1559-4076 |
language | eng |
recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_2655843 |
source | MEDLINE; EZB-FREE-00999 freely available EZB journals; PubMed Central |
subjects | Algorithms Anti-HIV Agents - therapeutic use Databases as Topic Drug Resistance, Viral - genetics Genome, Viral HIV - genetics HIV Infections - drug therapy HIV Infections - virology Humans Information Storage and Retrieval - methods Knowledge Bases Longitudinal Studies Mutation Time User-Computer Interface Viral Load Vocabulary, Controlled |
title | An ontology-driven method for hierarchical mining of temporal patterns: application to HIV drug resistance research |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-24T11%3A59%3A59IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=An%20ontology-driven%20method%20for%20hierarchical%20mining%20of%20temporal%20patterns:%20application%20to%20HIV%20drug%20resistance%20research&rft.jtitle=AMIA%20...%20Annual%20Symposium%20proceedings&rft.au=Raj,%20Rashmi&rft.date=2007-10-11&rft.volume=2007&rft.spage=614&rft.epage=619&rft.pages=614-619&rft.eissn=1559-4076&rft_id=info:doi/&rft_dat=%3Cproquest_pubme%3E70142667%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=70142667&rft_id=info:pmid/18693909&rfr_iscdi=true |