{"id":"https://openalex.org/W2766234835","doi":"https://doi.org/10.1142/s0219720018400255","title":"A max-margin training of RNA secondary structure prediction integrated with the thermodynamic model","display_name":"A max-margin training of RNA secondary structure prediction integrated with the thermodynamic model","publication_year":2018,"publication_date":"2018-10-31","ids":{"openalex":"https://openalex.org/W2766234835","doi":"https://doi.org/10.1142/s0219720018400255","mag":"2766234835","pmid":"https://pubmed.ncbi.nlm.nih.gov/30616476"},"language":"en","primary_location":{"id":"doi:10.1142/s0219720018400255","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219720018400255","pdf_url":null,"source":{"id":"https://openalex.org/S155349577","display_name":"Journal of Bioinformatics and Computational Biology","issn_l":"0219-7200","issn":["0219-7200","1757-6334"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311754","host_organization_name":"Imperial College Press","host_organization_lineage":["https://openalex.org/P4310311754"],"host_organization_lineage_names":["Imperial College Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Bioinformatics and Computational Biology","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/A5082419201","display_name":"Manato Akiyama","orcid":"https://orcid.org/0000-0002-5177-3199"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Manato Akiyama","raw_affiliation_strings":["Department of Biosciences and Informatics, Keio University, 3\u201314\u20131 Hiyoshi, Kohoku-ku, Yokohama 223\u20138522, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biosciences and Informatics, Keio University, 3\u201314\u20131 Hiyoshi, Kohoku-ku, Yokohama 223\u20138522, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076175043","display_name":"Kengo Sato","orcid":"https://orcid.org/0000-0001-6744-7390"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Kengo Sato","raw_affiliation_strings":["Department of Biosciences and Informatics, Keio University, 3\u201314\u20131 Hiyoshi, Kohoku-ku, Yokohama 223\u20138522, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biosciences and Informatics, Keio University, 3\u201314\u20131 Hiyoshi, Kohoku-ku, Yokohama 223\u20138522, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025573915","display_name":"Yasubumi Sakakibara","orcid":"https://orcid.org/0000-0002-6932-3452"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yasubumi Sakakibara","raw_affiliation_strings":["Department of Biosciences and Informatics, Keio University, 3\u201314\u20131 Hiyoshi, Kohoku-ku, Yokohama 223\u20138522, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biosciences and Informatics, Keio University, 3\u201314\u20131 Hiyoshi, Kohoku-ku, Yokohama 223\u20138522, Japan","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5076175043"],"corresponding_institution_ids":["https://openalex.org/I203951103"],"apc_list":null,"apc_paid":null,"fwci":1.1131,"has_fulltext":false,"cited_by_count":58,"citation_normalized_percentile":{"value":0.76802739,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"16","issue":"06","first_page":"1840025","last_page":"1840025"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10521","display_name":"RNA and protein synthesis mechanisms","score":1.0,"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/T10521","display_name":"RNA and protein synthesis mechanisms","score":1.0,"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/T11482","display_name":"RNA modifications and cancer","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/T10604","display_name":"RNA Research and Splicing","score":0.9980999827384949,"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/overfitting","display_name":"Overfitting","score":0.948096513748169},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7138225436210632},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.702514111995697},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6940068602561951},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6194364428520203},{"id":"https://openalex.org/keywords/structural-risk-minimization","display_name":"Structural risk minimization","score":0.6024343967437744},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.580315113067627},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5553311109542847},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5340501070022583},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35918304324150085},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.25105515122413635}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.948096513748169},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7138225436210632},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.702514111995697},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6940068602561951},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6194364428520203},{"id":"https://openalex.org/C154507838","wikidata":"https://www.wikidata.org/wiki/Q7625053","display_name":"Structural risk minimization","level":3,"score":0.6024343967437744},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.580315113067627},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5553311109542847},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5340501070022583},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35918304324150085},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25105515122413635},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","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":true},{"descriptor_ui":"D008958","descriptor_name":"Models, Molecular","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008958","descriptor_name":"Models, Molecular","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009690","descriptor_name":"Nucleic Acid Conformation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009690","descriptor_name":"Nucleic Acid Conformation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009690","descriptor_name":"Nucleic Acid Conformation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012313","descriptor_name":"RNA","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D012313","descriptor_name":"RNA","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D012313","descriptor_name":"RNA","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D013816","descriptor_name":"Thermodynamics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013816","descriptor_name":"Thermodynamics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013816","descriptor_name":"Thermodynamics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D030561","descriptor_name":"Databases, Nucleic Acid","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D030561","descriptor_name":"Databases, Nucleic Acid","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D030561","descriptor_name":"Databases, Nucleic Acid","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:10.1142/s0219720018400255","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219720018400255","pdf_url":null,"source":{"id":"https://openalex.org/S155349577","display_name":"Journal of Bioinformatics and Computational Biology","issn_l":"0219-7200","issn":["0219-7200","1757-6334"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311754","host_organization_name":"Imperial College Press","host_organization_lineage":["https://openalex.org/P4310311754"],"host_organization_lineage_names":["Imperial College Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Bioinformatics and Computational Biology","raw_type":"journal-article"},{"id":"pmid:30616476","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30616476","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":"Journal of bioinformatics and computational biology","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8100000023841858,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320312060","display_name":"Francis Crick Institute","ror":"https://ror.org/04tnbqb63"},{"id":"https://openalex.org/F4320320912","display_name":"Ministry of Education, Culture, Sports, Science and Technology","ror":"https://ror.org/048rj2z13"},{"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":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1603840783","https://openalex.org/W1861164398","https://openalex.org/W1965243792","https://openalex.org/W1981576666","https://openalex.org/W1984675364","https://openalex.org/W1994958179","https://openalex.org/W2006936482","https://openalex.org/W2011368877","https://openalex.org/W2016614259","https://openalex.org/W2017313617","https://openalex.org/W2020546070","https://openalex.org/W2023206235","https://openalex.org/W2025763720","https://openalex.org/W2031352989","https://openalex.org/W2045895660","https://openalex.org/W2049283139","https://openalex.org/W2052080622","https://openalex.org/W2064714768","https://openalex.org/W2086561953","https://openalex.org/W2098571862","https://openalex.org/W2101497682","https://openalex.org/W2102017611","https://openalex.org/W2105842272","https://openalex.org/W2109638684","https://openalex.org/W2113816707","https://openalex.org/W2130682154","https://openalex.org/W2134489577","https://openalex.org/W2142038007","https://openalex.org/W2146721220","https://openalex.org/W2147013647","https://openalex.org/W2159117141","https://openalex.org/W2160515562","https://openalex.org/W2169185001","https://openalex.org/W2396723088"],"related_works":["https://openalex.org/W4238478255","https://openalex.org/W2358191590","https://openalex.org/W2009251346","https://openalex.org/W1977818193","https://openalex.org/W2547190668","https://openalex.org/W2379140333","https://openalex.org/W2125871051","https://openalex.org/W2792286724","https://openalex.org/W2122015339","https://openalex.org/W2389264710"],"abstract_inverted_index":{"A":[0],"popular":[1],"approach":[2,31,45,109],"for":[3,85,100,132],"predicting":[4],"RNA":[5,101],"secondary":[6,19,102],"structure":[7,20,103],"is":[8,33,182],"the":[9,58,62,81,107,111,120,141,148,163],"thermodynamic":[10,108,123],"nearest-neighbor":[11],"model":[12,50,70,88,118],"that":[13,32,51,105,137,159],"finds":[14],"a":[15,48,66,78,87,97,126],"thermodynamically":[16],"most":[17],"stable":[18],"with":[21,57,125,147,168],"minimum":[22],"free":[23],"energy":[24],"(MFE).":[25],"For":[26],"further":[27],"improvement,":[28],"an":[29],"alternative":[30],"based":[34],"on":[35],"machine":[36,43,67,112,145],"learning":[37],"techniques":[38],"has":[39,89],"been":[40,90],"developed.":[41],"The":[42,177],"learning-based":[44,68,113],"can":[46],"employ":[47],"fine-grained":[49,69,117],"includes":[52],"much":[53],"richer":[54],"feature":[55],"representations":[56],"ability":[59],"to":[60,153],"fit":[61],"training":[63],"data.":[64],"Although":[65],"achieved":[71],"extremely":[72],"high":[73],"performance":[74],"in":[75],"prediction":[76,104,165],"accuracy,":[77],"possibility":[79],"of":[80,83,129,135,179],"risk":[82],"overfitting":[84,173],"such":[86],"reported.":[91],"In":[92],"this":[93],"paper,":[94],"we":[95],"propose":[96],"novel":[98],"algorithm":[99,161,181],"integrates":[106],"and":[110,171],"weighted":[114],"approach.":[115],"Our":[116,156],"combines":[119],"experimentally":[121],"determined":[122],"parameters":[124,131],"large":[127],"number":[128],"scoring":[130],"detailed":[133],"contexts":[134],"features":[136],"are":[138],"trained":[139],"by":[140],"structured":[142],"support":[143],"vector":[144],"(SSVM)":[146],"[Formula:":[149],"see":[150],"text]":[151],"regularization":[152],"avoid":[154],"overfitting.":[155],"benchmark":[157],"shows":[158],"our":[160,180],"achieves":[162],"best":[164],"accuracy":[166],"compared":[167],"existing":[169],"methods,":[170],"heavy":[172],"cannot":[174],"be":[175],"observed.":[176],"implementation":[178],"available":[183],"at":[184],"https://github.com/keio-bioinformatics/mxfold":[185],".":[186]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}