{"id":"https://openalex.org/W2104703176","doi":"https://doi.org/10.1093/bioinformatics/btq700","title":"DROP: an SVM domain linker predictor trained with optimal features selected by random forest","display_name":"DROP: an SVM domain linker predictor trained with optimal features selected by random forest","publication_year":2010,"publication_date":"2010-12-17","ids":{"openalex":"https://openalex.org/W2104703176","doi":"https://doi.org/10.1093/bioinformatics/btq700","mag":"2104703176","pmid":"https://pubmed.ncbi.nlm.nih.gov/21169376"},"language":"en","primary_location":{"id":"doi:10.1093/bioinformatics/btq700","is_oa":true,"landing_page_url":"https://doi.org/10.1093/bioinformatics/btq700","pdf_url":"https://academic.oup.com/bioinformatics/article-pdf/27/4/487/48863928/bioinformatics_27_4_487.pdf","source":{"id":"https://openalex.org/S52395412","display_name":"Bioinformatics","issn_l":"1367-4803","issn":["1367-4803","1367-4811"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://academic.oup.com/bioinformatics/article-pdf/27/4/487/48863928/bioinformatics_27_4_487.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015640042","display_name":"Teppei Ebina","orcid":"https://orcid.org/0000-0002-3097-0513"},"institutions":[{"id":"https://openalex.org/I92614990","display_name":"Tokyo University of Agriculture and Technology","ror":"https://ror.org/00qg0kr10","country_code":"JP","type":"education","lineage":["https://openalex.org/I92614990"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Teppei Ebina","raw_affiliation_strings":["1 Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 12-24-16 Nakamachi, Koganei-shi, Tokyo 184-8588, Japan and 2Computational Biology Research Center, AIST Tokyo Waterfront Bio-IT Research Building 2-4-7 Aomi, Koto-ku, Tokyo, 135-0064, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"1 Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 12-24-16 Nakamachi, Koganei-shi, Tokyo 184-8588, Japan and 2Computational Biology Research Center, AIST Tokyo Waterfront Bio-IT Research Building 2-4-7 Aomi, Koto-ku, Tokyo, 135-0064, Japan","institution_ids":["https://openalex.org/I92614990"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106184369","display_name":"Hiroyuki Toh","orcid":null},"institutions":[{"id":"https://openalex.org/I92614990","display_name":"Tokyo University of Agriculture and Technology","ror":"https://ror.org/00qg0kr10","country_code":"JP","type":"education","lineage":["https://openalex.org/I92614990"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Hiroyuki Toh","raw_affiliation_strings":["1 Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 12-24-16 Nakamachi, Koganei-shi, Tokyo 184-8588, Japan and 2Computational Biology Research Center, AIST Tokyo Waterfront Bio-IT Research Building 2-4-7 Aomi, Koto-ku, Tokyo, 135-0064, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"1 Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 12-24-16 Nakamachi, Koganei-shi, Tokyo 184-8588, Japan and 2Computational Biology Research Center, AIST Tokyo Waterfront Bio-IT Research Building 2-4-7 Aomi, Koto-ku, Tokyo, 135-0064, Japan","institution_ids":["https://openalex.org/I92614990"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010639542","display_name":"Yutaka Kuroda","orcid":"https://orcid.org/0000-0002-3221-4295"},"institutions":[{"id":"https://openalex.org/I92614990","display_name":"Tokyo University of Agriculture and Technology","ror":"https://ror.org/00qg0kr10","country_code":"JP","type":"education","lineage":["https://openalex.org/I92614990"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yutaka Kuroda","raw_affiliation_strings":["1 Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 12-24-16 Nakamachi, Koganei-shi, Tokyo 184-8588, Japan and 2Computational Biology Research Center, AIST Tokyo Waterfront Bio-IT Research Building 2-4-7 Aomi, Koto-ku, Tokyo, 135-0064, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"1 Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 12-24-16 Nakamachi, Koganei-shi, Tokyo 184-8588, Japan and 2Computational Biology Research Center, AIST Tokyo Waterfront Bio-IT Research Building 2-4-7 Aomi, Koto-ku, Tokyo, 135-0064, Japan","institution_ids":["https://openalex.org/I92614990"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5010639542","https://openalex.org/A5106184369"],"corresponding_institution_ids":["https://openalex.org/I92614990"],"apc_list":{"value":3618,"currency":"USD","value_usd":3618},"apc_paid":null,"fwci":1.7452,"has_fulltext":false,"cited_by_count":68,"citation_normalized_percentile":{"value":0.84094796,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"27","issue":"4","first_page":"487","last_page":"494"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9988999962806702,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9988999962806702,"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":0.9983000159263611,"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"}},{"id":"https://openalex.org/T10015","display_name":"Genomics and Phylogenetic Studies","score":0.9962000250816345,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7989569902420044},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7515977621078491},{"id":"https://openalex.org/keywords/linker","display_name":"Linker","score":0.6946846842765808},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6779888868331909},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6768608689308167},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5142828822135925},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48294442892074585},{"id":"https://openalex.org/keywords/drop","display_name":"Drop (telecommunication)","score":0.4594183564186096},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.445600688457489},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4313458204269409},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37140288949012756},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3693919777870178},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14504167437553406}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7989569902420044},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7515977621078491},{"id":"https://openalex.org/C2780557392","wikidata":"https://www.wikidata.org/wiki/Q523796","display_name":"Linker","level":2,"score":0.6946846842765808},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6779888868331909},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6768608689308167},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5142828822135925},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48294442892074585},{"id":"https://openalex.org/C2781345722","wikidata":"https://www.wikidata.org/wiki/Q5308388","display_name":"Drop (telecommunication)","level":2,"score":0.4594183564186096},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.445600688457489},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4313458204269409},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37140288949012756},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3693919777870178},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14504167437553406},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000032","qualifier_name":"analysis","is_major_topic":false},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000032","qualifier_name":"analysis","is_major_topic":false},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000032","qualifier_name":"analysis","is_major_topic":false},{"descriptor_ui":"D017433","descriptor_name":"Protein Structure, Secondary","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D017433","descriptor_name":"Protein Structure, Secondary","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D017433","descriptor_name":"Protein Structure, Secondary","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D040901","descriptor_name":"Proteomics","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D040901","descriptor_name":"Proteomics","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D040901","descriptor_name":"Proteomics","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1093/bioinformatics/btq700","is_oa":true,"landing_page_url":"https://doi.org/10.1093/bioinformatics/btq700","pdf_url":"https://academic.oup.com/bioinformatics/article-pdf/27/4/487/48863928/bioinformatics_27_4_487.pdf","source":{"id":"https://openalex.org/S52395412","display_name":"Bioinformatics","issn_l":"1367-4803","issn":["1367-4803","1367-4811"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bioinformatics","raw_type":"journal-article"},{"id":"pmid:21169376","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/21169376","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bioinformatics (Oxford, England)","raw_type":null}],"best_oa_location":{"id":"doi:10.1093/bioinformatics/btq700","is_oa":true,"landing_page_url":"https://doi.org/10.1093/bioinformatics/btq700","pdf_url":"https://academic.oup.com/bioinformatics/article-pdf/27/4/487/48863928/bioinformatics_27_4_487.pdf","source":{"id":"https://openalex.org/S52395412","display_name":"Bioinformatics","issn_l":"1367-4803","issn":["1367-4803","1367-4811"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bioinformatics","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.7599999904632568}],"awards":[{"id":"https://openalex.org/G5800533764","display_name":"Development of a novel amino acid solubility propensity scale for the calculation of polypeptide solubility","funder_award_id":"21300110","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2104703176.pdf"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W11646241","https://openalex.org/W273955616","https://openalex.org/W1542067597","https://openalex.org/W1543010007","https://openalex.org/W1568513966","https://openalex.org/W1576520375","https://openalex.org/W1604726175","https://openalex.org/W1604938182","https://openalex.org/W1973262365","https://openalex.org/W1977779119","https://openalex.org/W1987468852","https://openalex.org/W1988848004","https://openalex.org/W2006796203","https://openalex.org/W2010483820","https://openalex.org/W2027446338","https://openalex.org/W2043338013","https://openalex.org/W2057497070","https://openalex.org/W2083468430","https://openalex.org/W2089262030","https://openalex.org/W2097932035","https://openalex.org/W2107441346","https://openalex.org/W2110779321","https://openalex.org/W2111374837","https://openalex.org/W2116772258","https://openalex.org/W2119387367","https://openalex.org/W2126975650","https://openalex.org/W2127338593","https://openalex.org/W2130647858","https://openalex.org/W2134327751","https://openalex.org/W2138953240","https://openalex.org/W2140628140","https://openalex.org/W2141595346","https://openalex.org/W2141885858","https://openalex.org/W2146512686","https://openalex.org/W2147923983","https://openalex.org/W2149548330","https://openalex.org/W2152059523","https://openalex.org/W2153187042","https://openalex.org/W2155144535","https://openalex.org/W2165544410","https://openalex.org/W6610017368","https://openalex.org/W6632556893","https://openalex.org/W6634442568"],"related_works":["https://openalex.org/W4200112873","https://openalex.org/W2955796858","https://openalex.org/W4224941037","https://openalex.org/W2004826645","https://openalex.org/W3135818052","https://openalex.org/W4388745254","https://openalex.org/W2980082554","https://openalex.org/W2767419625","https://openalex.org/W2389704471","https://openalex.org/W1517228774"],"abstract_inverted_index":{"MOTIVATION:":[0],"Biologically":[1],"important":[2],"proteins":[3,34,141],"are":[4,10,21],"often":[5],"large,":[6],"multidomain":[7,140],"proteins,":[8],"which":[9,57,144],"difficult":[11],"to":[12],"characterize":[13],"by":[14,170],"high-throughput":[15],"experimental":[16],"methods.":[17],"Efficient":[18],"domain/boundary":[19],"predictions":[20],"thus":[22],"increasingly":[23],"required":[24],"in":[25,136],"diverse":[26],"area":[27],"of":[28,67,74,95,108,120,130,149,164],"proteomics":[29],"research":[30],"for":[31,132],"computationally":[32],"dissecting":[33],"into":[35],"readily":[36],"analyzable":[37],"domains.":[38],"RESULTS:":[39],"We":[40],"constructed":[41],"a":[42,72,78,84,90],"support":[43],"vector":[44],"machine":[45],"(SVM)-based":[46],"domain":[47,165],"linker":[48,52,177],"predictor,":[49],"DROP":[50,88,131],"(Domain":[51],"pRediction":[53],"using":[54,77],"OPtimal":[55],"features),":[56],"was":[58,69,142,145],"trained":[59,112],"with":[60,83,113],"25":[61],"optimal":[62,65,172],"features.":[63],"The":[64],"combination":[66],"features":[68,76,173],"identified":[70],"from":[71,178],"set":[73],"3000":[75],"random":[79],"forest":[80],"algorithm":[81],"complemented":[82],"stepwise":[85],"feature":[86,122],"selection.":[87],"demonstrated":[89],"prediction":[91,163],"sensitivity":[92],"and":[93,97],"precision":[94],"41.3":[96],"49.4%,":[98],"respectively.":[99],"These":[100],"values":[101],"were":[102],"over":[103],"19.9%":[104],"higher":[105,146],"than":[106,147],"those":[107],"control":[109],"SVM":[110,162],"predictors":[111],"non-optimized":[114],"features,":[115],"strongly":[116],"suggesting":[117],"the":[118,127,150,161],"efficiency":[119],"our":[121],"selection":[123],"method.":[124],"In":[125],"addition,":[126],"mean":[128],"NDO-Score":[129],"predicting":[133],"novel":[134],"domains":[135],"seven":[137],"CASP8":[138,153],"FM":[139],"0.760,":[143],"any":[148],"12":[151],"published":[152],"DP":[154],"servers.":[155],"Overall,":[156],"these":[157],"results":[158],"indicate":[159],"that":[160,174],"linkers":[166],"can":[167],"be":[168],"improved":[169],"identifying":[171],"best":[175],"distinguish":[176],"non-linker":[179],"regions.":[180]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":9},{"year":2015,"cited_by_count":9},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":7},{"year":2012,"cited_by_count":4}],"updated_date":"2026-07-09T07:52:08.696243","created_date":"2025-10-10T00:00:00"}
