{"id":"https://openalex.org/W2911833392","doi":"https://doi.org/10.1109/cisp-bmei.2018.8633098","title":"Protein Subnuclear Localization Using a Hybrid Classifier Combined with Chou's Pseudo Amino Acid Composition","display_name":"Protein Subnuclear Localization Using a Hybrid Classifier Combined with Chou's Pseudo Amino Acid Composition","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2911833392","doi":"https://doi.org/10.1109/cisp-bmei.2018.8633098","mag":"2911833392"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei.2018.8633098","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2018.8633098","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5027164530","display_name":"Chaohong Song","orcid":null},"institutions":[{"id":"https://openalex.org/I204823248","display_name":"Huazhong Agricultural University","ror":"https://ror.org/023b72294","country_code":"CN","type":"education","lineage":["https://openalex.org/I204823248"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chaohong Song","raw_affiliation_strings":["College of science, Huazhong Agricultural University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"College of science, Huazhong Agricultural University, Wuhan, China","institution_ids":["https://openalex.org/I204823248"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5027164530"],"corresponding_institution_ids":["https://openalex.org/I204823248"],"apc_list":null,"apc_paid":null,"fwci":0.0919,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.49213686,"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":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9998999834060669,"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":0.9998999834060669,"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/T10521","display_name":"RNA and protein synthesis mechanisms","score":0.9940000176429749,"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/T10044","display_name":"Protein Structure and Dynamics","score":0.9918000102043152,"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/pseudo-amino-acid-composition","display_name":"Pseudo amino acid composition","score":0.8907790184020996},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6482643485069275},{"id":"https://openalex.org/keywords/subcellular-localization","display_name":"Subcellular localization","score":0.5718896389007568},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5668071508407593},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5643081068992615},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5015969276428223},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4935516119003296},{"id":"https://openalex.org/keywords/jackknife-resampling","display_name":"Jackknife resampling","score":0.4198739528656006},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4043843150138855},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.2800966799259186},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2701399326324463},{"id":"https://openalex.org/keywords/biochemistry","display_name":"Biochemistry","score":0.22278404235839844},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1185239851474762}],"concepts":[{"id":"https://openalex.org/C2780362125","wikidata":"https://www.wikidata.org/wiki/Q7254464","display_name":"Pseudo amino acid composition","level":4,"score":0.8907790184020996},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6482643485069275},{"id":"https://openalex.org/C2776879804","wikidata":"https://www.wikidata.org/wiki/Q7630919","display_name":"Subcellular localization","level":3,"score":0.5718896389007568},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5668071508407593},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5643081068992615},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5015969276428223},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4935516119003296},{"id":"https://openalex.org/C81790035","wikidata":"https://www.wikidata.org/wiki/Q847158","display_name":"Jackknife resampling","level":3,"score":0.4198739528656006},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4043843150138855},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.2800966799259186},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2701399326324463},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.22278404235839844},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1185239851474762},{"id":"https://openalex.org/C190062978","wikidata":"https://www.wikidata.org/wiki/Q79899","display_name":"Cytoplasm","level":2,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei.2018.8633098","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2018.8633098","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1918744929","https://openalex.org/W1970068990","https://openalex.org/W1977852743","https://openalex.org/W1977927254","https://openalex.org/W1989298127","https://openalex.org/W2020194549","https://openalex.org/W2021408532","https://openalex.org/W2043976158","https://openalex.org/W2047444359","https://openalex.org/W2053963319","https://openalex.org/W2075603481","https://openalex.org/W2077204677","https://openalex.org/W2077467360","https://openalex.org/W2082627972","https://openalex.org/W2088117005","https://openalex.org/W2101365596","https://openalex.org/W2122554885","https://openalex.org/W2144620643","https://openalex.org/W2146146101","https://openalex.org/W2150047146","https://openalex.org/W2207974024","https://openalex.org/W2520558288","https://openalex.org/W2540579902","https://openalex.org/W2560732228","https://openalex.org/W2570387740","https://openalex.org/W2770878209","https://openalex.org/W2772162964"],"related_works":["https://openalex.org/W4323320301","https://openalex.org/W2620675477","https://openalex.org/W2144607908","https://openalex.org/W1984511561","https://openalex.org/W2151425463","https://openalex.org/W2053963319","https://openalex.org/W2942524405","https://openalex.org/W2752562526","https://openalex.org/W2085022192","https://openalex.org/W1816488618"],"abstract_inverted_index":{"Protein":[0],"subnuclear":[1,24,50,76,90,147],"localization":[2,25],"is":[3],"very":[4],"important":[5,21,164],"for":[6,145,156],"biology":[7],"research":[8],"and":[9,14,61,92,117,143,149,160,172],"medicine":[10],"design.":[11],"Feature":[12],"extraction":[13,58],"the":[15,27,41,80,110,118,167],"classifier":[16,71,97],"selection":[17],"are":[18],"two":[19],"most":[20],"aspects":[22],"in":[23,47,52,88,166],"prediction,":[26],"efficiency":[28],"of":[29,43,59,64,103,122,130,169],"their":[30],"cooperation":[31],"role":[32,165],"directly":[33],"decides":[34],"prediction":[35],"accuracy.":[36],"Giving":[37],"full":[38],"play":[39,162],"to":[40,73],"advantages":[42],"support":[44],"vector":[45],"machine":[46],"forecasting":[48],"protein":[49,75,146,158],"localizations,":[51],"this":[53],"study,":[54],"jointly":[55],"using":[56],"multi-feature":[57],"proteins":[60,86],"dimension":[62],"reduction":[63],"laplacian":[65],"eigenmaps,":[66],"we":[67],"designed":[68],"a":[69,153],"promising":[70],"system":[72,98],"predict":[74],"localization.":[77],"Testing":[78],"on":[79],"benchmark":[81],"dataset":[82],"which":[83,105],"contained":[84],"714":[85],"localized":[87],"nine":[89,123],"compartments,":[91],"applying":[93],"jackknife":[94],"test,":[95],"our":[96,139],"could":[99],"obtain":[100],"total":[101],"accuracy":[102],"81.23%,":[104],"was":[106,141],"obviously":[107],"higher":[108,127],"than":[109,128],"results":[111],"that":[112,138],"had":[113],"been":[114],"obtained":[115],"before,":[116],"Matthews":[119],"correlation":[120],"coefficients":[121],"compartments":[124],"were":[125],"also":[126],"those":[129],"previous":[131],"methods.":[132],"All":[133],"these":[134],"success":[135],"rates":[136],"showed":[137],"method":[140,155],"robust":[142],"effective":[144],"localization,":[148],"it":[150],"would":[151,161],"be":[152],"supplement":[154],"other":[157],"classification":[159],"an":[163],"fields":[168],"drug":[170],"design":[171],"pharmaceutical":[173],"industry.":[174]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}