{"id":"https://openalex.org/W2575899494","doi":"https://doi.org/10.1109/bibm.2016.7822519","title":"Metabolomic data deconvolution using probabilistic purification models","display_name":"Metabolomic data deconvolution using probabilistic purification models","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2575899494","doi":"https://doi.org/10.1109/bibm.2016.7822519","mag":"2575899494"},"language":"en","primary_location":{"id":"doi:10.1109/bibm.2016.7822519","doi":"https://doi.org/10.1109/bibm.2016.7822519","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm.2016.7822519","pdf_url":null,"source":{"id":"https://openalex.org/S4363607730","display_name":"IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074522619","display_name":"Minkun Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I184565670","display_name":"Georgetown University","ror":"https://ror.org/05vzafd60","country_code":"US","type":"education","lineage":["https://openalex.org/I184565670"]},{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Minkun Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering Virginia Tech, Arlington, Virginia","Department of Oncology, Georgetown University, Washington D.C., USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering Virginia Tech, Arlington, Virginia","institution_ids":["https://openalex.org/I859038795"]},{"raw_affiliation_string":"Department of Oncology, Georgetown University, Washington D.C., USA","institution_ids":["https://openalex.org/I184565670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076306764","display_name":"Cristina Di Poto","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I184565670","display_name":"Georgetown University","ror":"https://ror.org/05vzafd60","country_code":"US","type":"education","lineage":["https://openalex.org/I184565670"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cristina Di Poto","raw_affiliation_strings":["Department of Oncology, Georgetown University, Washington D.C., USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Oncology, Georgetown University, Washington D.C., USA","institution_ids":["https://openalex.org/I184565670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004962196","display_name":"Alessia Ferrarini","orcid":"https://orcid.org/0000-0002-4587-6095","observed_orcids":["https://orcid.org/0000-0002-4587-6095","https://orcid.org/0000-0002-5841-2302"]},"institutions":[{"id":"https://openalex.org/I184565670","display_name":"Georgetown University","ror":"https://ror.org/05vzafd60","country_code":"US","type":"education","lineage":["https://openalex.org/I184565670"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alessia Ferrarini","raw_affiliation_strings":["Department of Oncology, Georgetown University, Washington D.C., USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Oncology, Georgetown University, Washington D.C., USA","institution_ids":["https://openalex.org/I184565670"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Guoqiang Yu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guoqiang Yu","raw_affiliation_strings":["Department of Electrical and Computer Engineering Virginia Tech, Arlington, Virginia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering Virginia Tech, Arlington, Virginia","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025125310","display_name":"Habtom W. Ressom","orcid":"https://orcid.org/0000-0001-9296-2132","observed_orcids":["https://orcid.org/0000-0001-9296-2132"]},"institutions":[{"id":"https://openalex.org/I184565670","display_name":"Georgetown University","ror":"https://ror.org/05vzafd60","country_code":"US","type":"education","lineage":["https://openalex.org/I184565670"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Habtom W. Ressom","raw_affiliation_strings":["Department of Oncology, Georgetown University, Washington D.C., USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Oncology, Georgetown University, Washington D.C., USA","institution_ids":["https://openalex.org/I184565670"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.2633048,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"204","last_page":"209"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.001500000013038516,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10519","display_name":"Advanced Proteomics Techniques and Applications","score":0.00039999998989515007,"subfield":{"id":"https://openalex.org/subfields/1607","display_name":"Spectroscopy"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cancer-biomarker-discovery","display_name":"cancer biomarker discovery","score":0.7739999890327454},{"id":"https://openalex.org/keywords/liver-tissue","display_name":"liver tissue","score":0.5680000185966492},{"id":"https://openalex.org/keywords/liver-cirrhosis","display_name":"liver cirrhosis","score":0.8529999852180481},{"id":"https://openalex.org/keywords/lc-ms","display_name":"LC-MS","score":0.6690000295639038},{"id":"https://openalex.org/keywords/gas-chromatography-mass-spectrometry","display_name":"gas chromatography-mass spectrometry","score":1.0},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"noise reduction","score":0.6840000152587891},{"id":"https://openalex.org/keywords/metabolite-abundance","display_name":"metabolite abundance","score":0.39399999380111694},{"id":"https://openalex.org/keywords/tumor-versus-normal-tissue","display_name":"tumor versus normal tissue comparison","score":0.3930000066757202}],"concepts":[{"id":"https://openalex.org/C21565614","wikidata":"https://www.wikidata.org/wiki/Q12149006","display_name":"Metabolomics","level":2,"score":0.8135604858398438},{"id":"https://openalex.org/C124535831","wikidata":"https://www.wikidata.org/wiki/Q4915074","display_name":"Biomarker discovery","level":4,"score":0.6311323642730713},{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.5600968599319458},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.48969510197639465},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.45841285586357117},{"id":"https://openalex.org/C2781197716","wikidata":"https://www.wikidata.org/wiki/Q864574","display_name":"Biomarker","level":2,"score":0.4130754768848419},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4018840193748474},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.3199458718299866},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.29130131006240845},{"id":"https://openalex.org/C46111723","wikidata":"https://www.wikidata.org/wiki/Q471857","display_name":"Proteomics","level":3,"score":0.26956307888031006},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.2269420325756073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.10587772727012634},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.09212714433670044},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm.2016.7822519","doi":"https://doi.org/10.1109/bibm.2016.7822519","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm.2016.7822519","pdf_url":null,"source":{"id":"https://openalex.org/S4363607730","display_name":"IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.8560000061988831,"display_name":"Good health and well-being"}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W640136745","https://openalex.org/W1880262756","https://openalex.org/W1984359045","https://openalex.org/W2001265990","https://openalex.org/W2049624178","https://openalex.org/W2096801725","https://openalex.org/W2123153543","https://openalex.org/W2149423573","https://openalex.org/W2150575159","https://openalex.org/W2151373442","https://openalex.org/W2155388222","https://openalex.org/W2207072235","https://openalex.org/W2315438426","https://openalex.org/W2515965061"],"related_works":["https://openalex.org/W2207072235","https://openalex.org/W2515965061","https://openalex.org/W7223038699","https://openalex.org/W2468578197","https://openalex.org/W2171541462","https://openalex.org/W3158979632","https://openalex.org/W2056589270","https://openalex.org/W2096639177","https://openalex.org/W4386026101","https://openalex.org/W2400239373"],"abstract_inverted_index":{"Liquid":[0],"(or":[1],"gas)":[2],"chromatography":[3],"coupled":[4],"with":[5,22],"mass":[6],"spectrometry":[7],"(LC-MS":[8],"or":[9,45,66],"GC-MS)":[10],"allows":[11],"quantitative":[12,39],"comparison":[13],"of":[14,25,41,57,73,82,117,129,148,162],"biomolecular":[15],"abundance":[16],"in":[17,37,63,133,140,152,159],"biological":[18],"samples":[19],"to":[20,53,156],"help":[21],"the":[23,54,71,80,127,146,149,160],"discovery":[24,50,81],"candidate":[26],"biomarkers":[27],"for":[28,47],"complex":[29],"diseases":[30],"such":[31],"as":[32],"cancer.":[33],"A":[34],"fundamental":[35],"challenge":[36],"using":[38,120],"analysis":[40,116],"biomolecules":[42],"by":[43,115],"LC-MS":[44,122],"GC-MS":[46],"cancer":[48],"biomarker":[49],"is":[51],"owing":[52],"heterogeneous":[55],"nature":[56],"human":[58],"biospecimens.":[59],"Various":[60],"contaminations":[61],"present":[62],"cancerous":[64],"tissues":[65,119],"adjacent":[67],"non-cancerous":[68],"constituents":[69],"confound":[70],"characterization":[72],"molecular":[74],"expression":[75],"profiles":[76],"and":[77,110,123,137,173],"thus":[78],"hinder":[79],"reliable":[83],"biomarkers.":[84],"We":[85,125],"previously":[86],"applied":[87],"probabilistic":[88,104],"purification":[89,105,131],"model":[90],"on":[91,107],"a":[92],"relatively":[93],"small":[94],"sample-size":[95,109],"metabolomic":[96,112,141],"data.":[97,142],"In":[98],"this":[99],"study,":[100],"we":[101,144],"further":[102],"apply":[103],"models":[106,132,151],"larger":[108],"multi-group":[111],"datasets":[113],"acquired":[114],"liver":[118,165,171],"both":[121],"GC-MS.":[124],"demonstrate":[126],"advantages":[128],"incorporating":[130],"retrieving":[134],"underlying":[135],"sources":[136],"reduce":[138],"noise":[139],"Furthermore,":[143],"investigate":[145],"benefit":[147],"proposed":[150],"improving":[153],"our":[154],"ability":[155],"detect":[157],"changes":[158],"level":[161],"metabolites":[163],"among":[164],"tissue":[166],"from":[167],"multiple":[168],"groups":[169],"(tumor,":[170],"cirrhosis,":[172],"normal).":[174]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2017-01-26T00:00:00"}
