{"id":"https://openalex.org/W3010776531","doi":"https://doi.org/10.1109/tcbb.2020.2979430","title":"Enhanced Protein Structural Class Prediction Using Effective Feature Modeling and Ensemble of Classifiers","display_name":"Enhanced Protein Structural Class Prediction Using Effective Feature Modeling and Ensemble of Classifiers","publication_year":2020,"publication_date":"2020-03-09","ids":{"openalex":"https://openalex.org/W3010776531","doi":"https://doi.org/10.1109/tcbb.2020.2979430","mag":"3010776531","pmid":"https://pubmed.ncbi.nlm.nih.gov/32149653"},"language":"en","primary_location":{"id":"doi:10.1109/tcbb.2020.2979430","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcbb.2020.2979430","pdf_url":null,"source":{"id":"https://openalex.org/S36029991","display_name":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","issn_l":"1545-5963","issn":["1545-5963","1557-9964","2374-0043"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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/ACM Transactions on Computational Biology and Bioinformatics","raw_type":"journal-article"},"type":"article","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/A5024603420","display_name":"Sanjay Bankapur","orcid":"https://orcid.org/0000-0003-3982-3859"},"institutions":[{"id":"https://openalex.org/I11880225","display_name":"National Institute of Technology Karnataka","ror":"https://ror.org/01hz4v948","country_code":"IN","type":"education","lineage":["https://openalex.org/I11880225"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Sanjay Bankapur","raw_affiliation_strings":["Department of Information Technology, National Institute of Technology Karnataka, Surathkal, Mangalore, Karnataka, India"],"affiliations":[{"raw_affiliation_string":"Department of Information Technology, National Institute of Technology Karnataka, Surathkal, Mangalore, Karnataka, India","institution_ids":["https://openalex.org/I11880225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040815462","display_name":"Nagamma Patil","orcid":"https://orcid.org/0000-0001-9924-9559"},"institutions":[{"id":"https://openalex.org/I11880225","display_name":"National Institute of Technology Karnataka","ror":"https://ror.org/01hz4v948","country_code":"IN","type":"education","lineage":["https://openalex.org/I11880225"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nagamma Patil","raw_affiliation_strings":["Department of Information Technology, National Institute of Technology Karnataka, Surathkal, Mangalore, Karnataka, India"],"affiliations":[{"raw_affiliation_string":"Department of Information Technology, National Institute of Technology Karnataka, Surathkal, Mangalore, Karnataka, India","institution_ids":["https://openalex.org/I11880225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5024603420"],"corresponding_institution_ids":["https://openalex.org/I11880225"],"apc_list":null,"apc_paid":null,"fwci":0.6677,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.66702466,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"18","issue":"6","first_page":"2409","last_page":"2419"},"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/T10044","display_name":"Protein Structure and Dynamics","score":0.9948999881744385,"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/T10015","display_name":"Genomics and Phylogenetic Studies","score":0.9937000274658203,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7320053577423096},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.724586009979248},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6901872158050537},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6444942951202393},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6218867301940918},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6076072454452515},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5246348977088928},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.48925137519836426},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.4834352731704712},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.4718218743801117},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45685580372810364},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.45622923970222473},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.4550938308238983},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4101417660713196}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7320053577423096},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.724586009979248},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6901872158050537},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6444942951202393},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6218867301940918},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6076072454452515},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5246348977088928},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.48925137519836426},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.4834352731704712},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.4718218743801117},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45685580372810364},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.45622923970222473},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.4550938308238983},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4101417660713196},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000595","descriptor_name":"Amino Acid Sequence","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":false},{"descriptor_ui":"D000595","descriptor_name":"Amino Acid Sequence","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":false},{"descriptor_ui":"D000595","descriptor_name":"Amino Acid Sequence","qualifier_ui":"Q000235","qualifier_name":"genetics","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":"Q000145","qualifier_name":"classification","is_major_topic":true},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":true},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":true},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":true},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":true},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D017433","descriptor_name":"Protein Structure, Secondary","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":false},{"descriptor_ui":"D017433","descriptor_name":"Protein Structure, Secondary","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":false},{"descriptor_ui":"D017433","descriptor_name":"Protein Structure, Secondary","qualifier_ui":"Q000235","qualifier_name":"genetics","is_major_topic":false},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D019295","descriptor_name":"Computational Biology","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D020539","descriptor_name":"Sequence Analysis, Protein","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D020539","descriptor_name":"Sequence Analysis, Protein","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D020539","descriptor_name":"Sequence Analysis, Protein","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D030562","descriptor_name":"Databases, Protein","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D030562","descriptor_name":"Databases, Protein","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D030562","descriptor_name":"Databases, Protein","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/tcbb.2020.2979430","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcbb.2020.2979430","pdf_url":null,"source":{"id":"https://openalex.org/S36029991","display_name":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","issn_l":"1545-5963","issn":["1545-5963","1557-9964","2374-0043"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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/ACM Transactions on Computational Biology and Bioinformatics","raw_type":"journal-article"},{"id":"pmid:32149653","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32149653","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":"IEEE/ACM transactions on computational biology and bioinformatics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.550000011920929,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G5028243304","display_name":null,"funder_award_id":"KSTePS/VGST-RGS/F/GRD No.727/2017-18","funder_id":"https://openalex.org/F4320328620","funder_display_name":"Vision Group on Science and Technology"}],"funders":[{"id":"https://openalex.org/F4320328620","display_name":"Vision Group on Science and Technology","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":73,"referenced_works":["https://openalex.org/W149741886","https://openalex.org/W1143733298","https://openalex.org/W1554033342","https://openalex.org/W1601201751","https://openalex.org/W1614298861","https://openalex.org/W1967888993","https://openalex.org/W1969522492","https://openalex.org/W1980690213","https://openalex.org/W1981005463","https://openalex.org/W1986913015","https://openalex.org/W1989447327","https://openalex.org/W1995379550","https://openalex.org/W1998354148","https://openalex.org/W1998518361","https://openalex.org/W2002745879","https://openalex.org/W2009880031","https://openalex.org/W2017229033","https://openalex.org/W2020117329","https://openalex.org/W2022046926","https://openalex.org/W2027052738","https://openalex.org/W2028372188","https://openalex.org/W2030793934","https://openalex.org/W2034771831","https://openalex.org/W2061068513","https://openalex.org/W2062225859","https://openalex.org/W2070753511","https://openalex.org/W2076460489","https://openalex.org/W2078697068","https://openalex.org/W2080829141","https://openalex.org/W2083501076","https://openalex.org/W2085277871","https://openalex.org/W2087317522","https://openalex.org/W2089989707","https://openalex.org/W2093701091","https://openalex.org/W2094077114","https://openalex.org/W2099757084","https://openalex.org/W2101234009","https://openalex.org/W2104332903","https://openalex.org/W2105634619","https://openalex.org/W2108432201","https://openalex.org/W2113784134","https://openalex.org/W2116660088","https://openalex.org/W2125725297","https://openalex.org/W2128653811","https://openalex.org/W2142529984","https://openalex.org/W2148779882","https://openalex.org/W2153187042","https://openalex.org/W2158714788","https://openalex.org/W2161072217","https://openalex.org/W2163449716","https://openalex.org/W2178834907","https://openalex.org/W2250539671","https://openalex.org/W2253867202","https://openalex.org/W2347153915","https://openalex.org/W2533142962","https://openalex.org/W2602933836","https://openalex.org/W2626435434","https://openalex.org/W2783197164","https://openalex.org/W2807459510","https://openalex.org/W2811297572","https://openalex.org/W2896636431","https://openalex.org/W2904937174","https://openalex.org/W2910571528","https://openalex.org/W2915815599","https://openalex.org/W2963626623","https://openalex.org/W4241607140","https://openalex.org/W4248116825","https://openalex.org/W6636510571","https://openalex.org/W6652507476","https://openalex.org/W6675354045","https://openalex.org/W6685716696","https://openalex.org/W6719819555","https://openalex.org/W6829944800"],"related_works":["https://openalex.org/W2967733078","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W2885778889","https://openalex.org/W2766514146","https://openalex.org/W2885516856","https://openalex.org/W4289703016","https://openalex.org/W4310224730","https://openalex.org/W4296079469"],"abstract_inverted_index":{"Protein":[0],"Secondary":[1],"Structural":[2],"Class":[3],"(PSSC)":[4],"information":[5,103,157],"is":[6,37,67,226,252],"important":[7],"in":[8,55],"investigating":[9],"further":[10,227],"challenges":[11],"of":[12,25,32,57,88,95,118,122,135,158,165,174,214,245],"protein":[13,16,19,26,65],"sequences":[14,66,124],"like":[15],"fold":[17],"recognition,":[18],"tertiary":[20],"structure":[21],"prediction,":[22],"and":[23,39,83,92,144,169,184,199,208,219,254],"analysis":[24],"functions":[27],"for":[28],"drug":[29],"discovery.":[30],"Identification":[31],"PSSC":[33,62],"using":[34,125,171],"biological":[35],"methods":[36],"time-consuming":[38],"cost-intensive.":[40],"Several":[41],"computational":[42],"models":[43,259],"have":[44],"been":[45],"developed":[46],"to":[47,70],"predict":[48],"the":[49,58,116,123,142,155,262],"structural":[50,159],"class;":[51],"however,":[52],"they":[53],"lack":[54],"generalization":[56],"model.":[59],"Hence,":[60],"predicting":[61],"based":[63,149],"on":[64,115,194,229,260],"still":[68],"proving":[69],"be":[71],"an":[72,80,93,172,211,242],"uphill":[73],"task.":[74],"In":[75],"this":[76],"article,":[77],"we":[78],"proposed":[79,98,190,224,249],"effective,":[81],"novel":[82],"generalized":[84,250],"prediction":[85],"model":[86,191,225,251],"consisting":[87],"a":[89,230],"feature":[90,99],"modeling":[91,100],"ensemble":[94,173],"classifiers.":[96],"The":[97,161,189,223,248],"extracts":[101],"discriminating":[102],"(features)":[104],"by":[105],"leveraging":[106],"three":[107,175],"techniques:":[108],"(i)":[109],"Embedding":[110],"-":[111,132],"features":[112,138,150,166],"are":[113,139,151,167],"extracted":[114,140,152],"basis":[117],"spatial":[119],"residue":[120],"arrangements":[121],"word":[126],"embedding":[127],"approaches;":[128],"(ii)":[129],"SkipXGram":[130],"Bi-gram":[131],"various":[133],"sets":[134,164],"skipped":[136],"bi-gram":[137],"from":[141],"sequences;":[143],"(iii)":[145],"General":[146],"Statistical":[147],"(GS)":[148],"which":[153],"covers":[154],"global":[156],"sequences.":[160],"combined":[162],"effective":[163],"trained":[168],"classified":[170],"classifiers:":[176],"Support":[177],"Vector":[178],"Machine":[179],"(SVM),":[180],"Random":[181],"Forest":[182],"(RF),":[183],"Gradient":[185],"Boosting":[186],"Machines":[187],"(GBM).":[188],"when":[192],"assessed":[193],"five":[195,263],"benchmark":[196,264],"datasets":[197],"(high":[198],"low":[200,233],"sequence":[201],"similarity),":[202],"viz.":[203],"z277,":[204],"z498,":[205],"25PDB,":[206],"1189,":[207],"FC699,":[209],"reported":[210],"overall":[212,243],"accuracy":[213,244],"93.55,":[215],"97.58,":[216],"81.82,":[217],"81.11,":[218],"93.93":[220],"percent":[221],"respectively.":[222],"validated":[228],"large-scale":[231],"updated":[232],"similarity":[234],"(":[235],"\u2264":[236],"25%)":[237],"dataset,":[238],"where":[239],"it":[240],"achieved":[241],"81.11":[246],"percent.":[247],"robust":[253],"consistently":[255],"outperformed":[256],"several":[257],"state-of-the-art":[258],"all":[261],"datasets.":[265]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}