{"id":"https://openalex.org/W2138929157","doi":"https://doi.org/10.1109/tnb.2004.837906","title":"Improved Protein Secondary Structure Prediction Using Support Vector Machine With a New Encoding Scheme and an Advanced Tertiary Classifier","display_name":"Improved Protein Secondary Structure Prediction Using Support Vector Machine With a New Encoding Scheme and an Advanced Tertiary Classifier","publication_year":2004,"publication_date":"2004-12-01","ids":{"openalex":"https://openalex.org/W2138929157","doi":"https://doi.org/10.1109/tnb.2004.837906","mag":"2138929157","pmid":"https://pubmed.ncbi.nlm.nih.gov/15631138"},"language":"en","primary_location":{"id":"doi:10.1109/tnb.2004.837906","doi":"https://doi.org/10.1109/tnb.2004.837906","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnb.2004.837906","pdf_url":null,"source":{"id":"https://openalex.org/S187110076","display_name":"IEEE Transactions on NanoBioscience","issn_l":"1536-1241","issn":["1536-1241","1558-2639"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-b","doyens","jufo-1","medline","norway-1","poland-70","russia-white-list-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Nanobioscience","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","pubmed"],"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/A5113406139","display_name":"H.-J. Hu","orcid":"https://orcid.org/0000-0003-1155-6592","observed_orcids":["https://orcid.org/0000-0003-1155-6592"]},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"H.-J. Hu","raw_affiliation_strings":["Department of Computer Science, Georgia State University, Atlanta, GA 30303-4110, USA. jpark1808@earthlink.net","Department of Computer Science , Georgia State University , Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Georgia State University, Atlanta, GA 30303-4110, USA. jpark1808@earthlink.net","institution_ids":["https://openalex.org/I181565077"]},{"raw_affiliation_string":"Department of Computer Science , Georgia State University , Atlanta, GA, USA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101465265","display_name":"Yi Feng Pan","orcid":"https://orcid.org/0000-0002-2766-3096","observed_orcids":["https://orcid.org/0000-0002-2766-3096"]},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Y. Pan","raw_affiliation_strings":["Department of Computer Science, Georgia State University, Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Georgia State University, Atlanta, GA, USA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007378854","display_name":"Robert W. Harrison","orcid":"https://orcid.org/0000-0003-2449-1214","observed_orcids":["https://orcid.org/0000-0003-2449-1214"]},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"R. Harrison","raw_affiliation_strings":["Department of Computer Science and the Department of Biology, Georgia State University, Atlanta, GA, USA","Department of Computer Science , Georgia State University , Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and the Department of Biology, Georgia State University, Atlanta, GA, USA","institution_ids":["https://openalex.org/I181565077"]},{"raw_affiliation_string":"Department of Computer Science , Georgia State University , Atlanta, GA, USA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012396051","display_name":"Phang C. Tai","orcid":"https://orcid.org/0000-0003-4217-9531","observed_orcids":["https://orcid.org/0000-0003-4217-9531"]},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"P.C. Tai","raw_affiliation_strings":["Department of Biology, Georgia State University, Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biology, Georgia State University, Atlanta, GA, USA","institution_ids":["https://openalex.org/I181565077"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I181565077"],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":2.4411,"has_fulltext":false,"cited_by_count":96,"citation_normalized_percentile":{"value":0.89604323,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"3","issue":"4","first_page":"265","last_page":"271"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.7207000255584717,"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/T10044","display_name":"Protein Structure and Dynamics","score":0.7207000255584717,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.2734000086784363,"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/T12946","display_name":"Fractal and DNA sequence analysis","score":0.0005000000237487257,"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/protein-secondary-structure-prediction","display_name":"secondary structure prediction","score":1.0},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.9800000190734863},{"id":"https://openalex.org/keywords/encoding-scheme","display_name":"encoding scheme","score":0.6240000128746033},{"id":"https://openalex.org/keywords/sliding-window-length","display_name":"sliding window length","score":0.5210000276565552}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.884285569190979},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.726081132888794},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.6774840354919434},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6608538627624512},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6554357409477234},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.61720871925354},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.580984354019165},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.5560601353645325},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4572155475616455},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.41538581252098083},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4114556312561035},{"id":"https://openalex.org/C125168437","wikidata":"https://www.wikidata.org/wiki/Q7625184","display_name":"Structured support vector machine","level":3,"score":0.4112429618835449},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23544296622276306},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000595","descriptor_name":"Amino Acid Sequence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008956","descriptor_name":"Models, Chemical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008958","descriptor_name":"Models, Molecular","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008969","descriptor_name":"Molecular Sequence Data","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011487","descriptor_name":"Protein Conformation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":true},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D016415","descriptor_name":"Sequence Alignment","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D017433","descriptor_name":"Protein Structure, Secondary","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D017434","descriptor_name":"Protein Structure, Tertiary","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D020539","descriptor_name":"Sequence Analysis, Protein","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":3,"locations":[{"id":"doi:10.1109/tnb.2004.837906","doi":"https://doi.org/10.1109/tnb.2004.837906","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnb.2004.837906","pdf_url":null,"source":{"id":"https://openalex.org/S187110076","display_name":"IEEE Transactions on NanoBioscience","issn_l":"1536-1241","issn":["1536-1241","1558-2639"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-b","doyens","jufo-1","medline","norway-1","poland-70","russia-white-list-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Nanobioscience","raw_type":"journal-article"},{"id":"pmid:15631138","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/15631138","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,"listed_in":[],"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":"IEEE transactions on nanobioscience","raw_type":"Comparative Study"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.130.8318","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.130.8318","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.gsu.edu/~cscyip/papers/ieeetnb04.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G259393761","display_name":null,"funder_award_id":"R01 GM34766-17S1","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"},{"id":"https://openalex.org/G544350796","display_name":"Protein translocation across Escherichia coli membranes","funder_award_id":"R01GM034766","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"},{"id":"https://openalex.org/G6952773419","display_name":"Georgia State University Biomedical Computing Center","funder_award_id":"P20GM065762","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"}],"funders":[{"id":"https://openalex.org/F4320337354","display_name":"National Institute of General Medical Sciences","ror":"https://ror.org/04q48ey07"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1563088657","https://openalex.org/W1966849089","https://openalex.org/W1985818354","https://openalex.org/W2008708467","https://openalex.org/W2012334384","https://openalex.org/W2013136212","https://openalex.org/W2041369927","https://openalex.org/W2100890997","https://openalex.org/W2111193871","https://openalex.org/W2122945697","https://openalex.org/W2141920771","https://openalex.org/W2143210482","https://openalex.org/W2147905080","https://openalex.org/W2171742422","https://openalex.org/W4239510810","https://openalex.org/W4254049456"],"related_works":["https://openalex.org/W2059658192","https://openalex.org/W2095802093","https://openalex.org/W7096946478","https://openalex.org/W656729520","https://openalex.org/W2128801478","https://openalex.org/W1595014273","https://openalex.org/W7099324759","https://openalex.org/W3195778380","https://openalex.org/W7098359805","https://openalex.org/W2100890997"],"abstract_inverted_index":{"Prediction":[0],"of":[1,18,68,86,140,162,176,189,201],"protein":[2],"secondary":[3,19,69],"structures":[4],"is":[5,23,39,58,107,119,155,180,185,209],"an":[6],"important":[7],"problem":[8],"in":[9,50,137,149,216],"bioinformatics":[10],"and":[11,71,83,90,114,182,207],"has":[12,46],"many":[13],"applications.":[14],"The":[15,36,132],"recent":[16],"trend":[17],"structure":[20,70],"prediction":[21,67,95,199],"studies":[22],"mostly":[24,47],"based":[25,121],"on":[26,122],"the":[27,31,66,94,98,138,141,147,151,160,163,174,183,195,197,212,217],"neural":[28],"network":[29],"or":[30],"support":[32],"vector":[33],"machine":[34,62],"(SVM).":[35],"SVM":[37,57,104,165],"method":[38],"a":[40,61,168],"comparatively":[41],"new":[42,116,169,202],"learning":[43,63],"system":[44],"which":[45,150,172],"been":[48],"used":[49,59],"pattern":[51],"recognition":[52],"problems.":[53],"In":[54],"this":[55,123,208],"study,":[56],"as":[60],"tool":[64],"for":[65,102],"several":[72],"encoding":[73,117],"schemes,":[74],"including":[75],"orthogonal":[76,153],"matrix,":[77,79,82],"hydrophobicity":[78],"BLOSUM62":[80],"substitution":[81],"combined":[84],"matrix":[85,154],"these,":[87],"are":[88],"applied":[89],"optimized":[91],"to":[92,158,194],"improve":[93],"accuracy.":[96],"Also,":[97],"optimal":[99,124],"window":[100,112,125],"length":[101],"six":[103,164],"binary":[105,142,166,178],"classifiers":[106,143,179],"established":[108],"by":[109],"testing":[110],"different":[111],"sizes":[113],"our":[115],"scheme":[118],"tested":[120],"size":[126],"via":[127],"sevenfold":[128],"cross":[129],"validation":[130],"tests.":[131],"results":[133,161,175],"show":[134],"2%":[135],"increase":[136],"accuracy":[139,200],"when":[144],"compared":[145,186],"with":[146,187],"instances":[148],"classical":[152],"used.":[156],"Finally,":[157],"combine":[159],"classifiers,":[167],"tertiary":[170,191,203],"classifier":[171,204],"combines":[173],"one-versus-one":[177],"introduced":[181],"performance":[184],"those":[188],"existing":[190],"classifiers.":[192],"According":[193],"results,":[196],"Q3":[198],"reaches":[205],"78.8%":[206],"better":[210],"than":[211],"best":[213],"result":[214],"reported":[215],"literature.":[218]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":9},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":5}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}