{"id":"https://openalex.org/W2767899184","doi":"https://doi.org/10.1109/icfsp.2017.8097057","title":"Improving peak detection by Gaussian mixture modeling of mass spectral signal","display_name":"Improving peak detection by Gaussian mixture modeling of mass spectral signal","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2767899184","doi":"https://doi.org/10.1109/icfsp.2017.8097057","mag":"2767899184"},"language":"en","primary_location":{"id":"doi:10.1109/icfsp.2017.8097057","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icfsp.2017.8097057","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 3rd International Conference on Frontiers of Signal Processing (ICFSP)","raw_type":"proceedings-article"},"type":"article","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/A5087940597","display_name":"Micha\u0142 Marczyk","orcid":"https://orcid.org/0000-0003-2508-5736"},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Michal Marczyk","raw_affiliation_strings":["Data Mining Group, Silesian University of Technology, Gliwice, Poland"],"affiliations":[{"raw_affiliation_string":"Data Mining Group, Silesian University of Technology, Gliwice, Poland","institution_ids":["https://openalex.org/I119004910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027451254","display_name":"Joanna Pola\u0144ska","orcid":null},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Joanna Polanska","raw_affiliation_strings":["Data Mining Group, Silesian University of Technology, Gliwice, Poland"],"affiliations":[{"raw_affiliation_string":"Data Mining Group, Silesian University of Technology, Gliwice, Poland","institution_ids":["https://openalex.org/I119004910"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062290220","display_name":"Andrzej Pola\u0144ski","orcid":"https://orcid.org/0000-0002-1793-9546"},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Andrzej Polanski","raw_affiliation_strings":["Institute of Informatics, Silesian University of Technology, Gliwice, Poland"],"affiliations":[{"raw_affiliation_string":"Institute of Informatics, Silesian University of Technology, Gliwice, Poland","institution_ids":["https://openalex.org/I119004910"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5087940597"],"corresponding_institution_ids":["https://openalex.org/I119004910"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.12608566,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"39","last_page":"43"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.998199999332428,"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":0.998199999332428,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10683","display_name":"Mass Spectrometry Techniques and Applications","score":0.9962999820709229,"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/mass-spectrum","display_name":"Mass spectrum","score":0.6115745306015015},{"id":"https://openalex.org/keywords/mass-spectrometry","display_name":"Mass spectrometry","score":0.6013795733451843},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5938116908073425},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.5251799821853638},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4918503761291504},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.48873472213745117},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.44713446497917175},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.44304215908050537},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.37181219458580017},{"id":"https://openalex.org/keywords/biological-system","display_name":"Biological system","score":0.3664396405220032},{"id":"https://openalex.org/keywords/analytical-chemistry","display_name":"Analytical Chemistry (journal)","score":0.3614134192466736},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34308356046676636},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.30602192878723145},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2577008605003357},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.14630767703056335}],"concepts":[{"id":"https://openalex.org/C40325409","wikidata":"https://www.wikidata.org/wiki/Q2360668","display_name":"Mass spectrum","level":3,"score":0.6115745306015015},{"id":"https://openalex.org/C162356407","wikidata":"https://www.wikidata.org/wiki/Q180809","display_name":"Mass spectrometry","level":2,"score":0.6013795733451843},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5938116908073425},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.5251799821853638},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4918503761291504},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.48873472213745117},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.44713446497917175},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.44304215908050537},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.37181219458580017},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.3664396405220032},{"id":"https://openalex.org/C113196181","wikidata":"https://www.wikidata.org/wiki/Q485223","display_name":"Analytical Chemistry (journal)","level":2,"score":0.3614134192466736},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34308356046676636},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.30602192878723145},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2577008605003357},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.14630767703056335},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C147597530","wikidata":"https://www.wikidata.org/wiki/Q369472","display_name":"Computational chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icfsp.2017.8097057","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icfsp.2017.8097057","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 3rd International Conference on Frontiers of Signal Processing (ICFSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1548955257","https://openalex.org/W1957776961","https://openalex.org/W2018914855","https://openalex.org/W2038856295","https://openalex.org/W2038885294","https://openalex.org/W2055254611","https://openalex.org/W2059544508","https://openalex.org/W2089326006","https://openalex.org/W2096878708","https://openalex.org/W2112248044","https://openalex.org/W2123989476","https://openalex.org/W2126897927","https://openalex.org/W2143773597","https://openalex.org/W2152379230","https://openalex.org/W2163845664","https://openalex.org/W2168130065","https://openalex.org/W2168175751","https://openalex.org/W2182800275","https://openalex.org/W2523877875","https://openalex.org/W2528404488","https://openalex.org/W4234589439","https://openalex.org/W6676789370"],"related_works":["https://openalex.org/W2382174632","https://openalex.org/W2129959498","https://openalex.org/W2784060934","https://openalex.org/W2902714807","https://openalex.org/W1975321310","https://openalex.org/W2537489131","https://openalex.org/W2394084632","https://openalex.org/W2358293514","https://openalex.org/W2077021924","https://openalex.org/W1578916557"],"abstract_inverted_index":{"In":[0,69,128,152],"recent":[1],"years":[2],"mass":[3,42,99,123,134],"spectrometry":[4,124],"became":[5],"the":[6,13,26,103,155],"leading":[7],"measurement":[8],"technique":[9],"in":[10],"proteomics,":[11],"giving":[12],"opportunity":[14],"to":[15],"construct":[16],"many":[17,112],"methods":[18],"for":[19,36],"detection":[20,67,76,105,146,150],"of":[21,30,41,98,118,133,144,157,159],"signal":[22],"peaks,":[23],"that":[24,94],"are":[25],"most":[27],"important":[28],"elements":[29],"each":[31,48],"spectrum.":[32],"An":[33],"efficient":[34],"approach":[35],"detecting":[37],"peaks":[38,120],"is":[39],"partitioning":[40,56],"spectrum":[43,100],"into":[44],"fragments":[45],"and":[46,82,121,139],"modeling":[47,97,132],"fragment":[49],"separately":[50],"using":[51,60,109],"Gaussian":[52,95],"mixture":[53,96,131],"decomposition.":[54],"The":[55],"may":[57],"be":[58],"obtained":[59,107],"unique":[61],"algorithm":[62,89],"or":[63],"any":[64],"existing":[65,110,148],"peak":[66,75,104,145,149,161],"method.":[68],"this":[70],"work":[71],"two":[72],"commonly":[73],"used":[74],"algorithms":[77],"were":[78,126],"examined,":[79],"namely":[80],"Cromwell":[81],"Mass":[83],"Spec":[84],"Wavelet.":[85],"Additionally,":[86],"a":[87],"built-in":[88],"was":[90,166],"proposed.":[91],"To":[92],"show":[93],"can":[101],"improve":[102],"performance":[106],"by":[108],"solutions,":[111],"synthetic":[113,129],"spectra":[114,135],"with":[115],"different":[116],"number":[117],"true":[119],"real":[122,153],"data":[125,130,154],"analyzed.":[127],"gave":[136],"higher":[137],"sensitivity":[138],"lower":[140],"false":[141],"discovery":[142],"rate":[143],"than":[147],"algorithms.":[151],"coefficient":[156],"variation":[158],"estimated":[160],"amplitude":[162],"among":[163],"biological":[164],"replicates":[165],"reduced.":[167]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}