{"id":"https://openalex.org/W2159262772","doi":"https://doi.org/10.1093/bioinformatics/btp421","title":"Prediction of protein \u03b2-residue contacts by Markov logic networks with grounding-specific weights","display_name":"Prediction of protein \u03b2-residue contacts by Markov logic networks with grounding-specific weights","publication_year":2009,"publication_date":"2009-07-09","ids":{"openalex":"https://openalex.org/W2159262772","doi":"https://doi.org/10.1093/bioinformatics/btp421","mag":"2159262772","pmid":"https://pubmed.ncbi.nlm.nih.gov/19592394"},"language":"en","primary_location":{"id":"doi:10.1093/bioinformatics/btp421","is_oa":false,"landing_page_url":"https://doi.org/10.1093/bioinformatics/btp421","pdf_url":null,"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":"green","oa_url":"http://hdl.handle.net/11380/1122687","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062424045","display_name":"Marco Lippi","orcid":"https://orcid.org/0000-0002-9663-1071"},"institutions":[{"id":"https://openalex.org/I45084792","display_name":"University of Florence","ror":"https://ror.org/04jr1s763","country_code":"IT","type":"education","lineage":["https://openalex.org/I45084792"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Marco Lippi","raw_affiliation_strings":["Machine Learning and Neural Networks Group, Dipartimento di Sistemi e Informatica, Universit\u00e0 degli Studi di Firenze, Via di Santa Marta 3, 50139 Firenze, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Machine Learning and Neural Networks Group, Dipartimento di Sistemi e Informatica, Universit\u00e0 degli Studi di Firenze, Via di Santa Marta 3, 50139 Firenze, Italy","institution_ids":["https://openalex.org/I45084792"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027422071","display_name":"Paolo Frasconi","orcid":"https://orcid.org/0000-0003-3117-9245"},"institutions":[{"id":"https://openalex.org/I45084792","display_name":"University of Florence","ror":"https://ror.org/04jr1s763","country_code":"IT","type":"education","lineage":["https://openalex.org/I45084792"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Paolo Frasconi","raw_affiliation_strings":["Machine Learning and Neural Networks Group, Dipartimento di Sistemi e Informatica, Universit\u00e0 degli Studi di Firenze, Via di Santa Marta 3, 50139 Firenze, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Machine Learning and Neural Networks Group, Dipartimento di Sistemi e Informatica, Universit\u00e0 degli Studi di Firenze, Via di Santa Marta 3, 50139 Firenze, Italy","institution_ids":["https://openalex.org/I45084792"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I45084792"],"apc_list":{"value":3618,"currency":"USD","value_usd":3618},"apc_paid":null,"fwci":1.3501,"has_fulltext":false,"cited_by_count":53,"citation_normalized_percentile":{"value":0.80484183,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"25","issue":"18","first_page":"2326","last_page":"2333"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.9778000116348267,"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":0.9778000116348267,"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":0.00430000014603138,"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/T10211","display_name":"Computational Drug Discovery Methods","score":0.002400000113993883,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/casp","display_name":"CASP","score":0.7630915641784668},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.638292670249939},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.6290347576141357},{"id":"https://openalex.org/keywords/statistical-relational-learning","display_name":"Statistical relational learning","score":0.5649879574775696},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5088768005371094},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4807955324649811},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.4401801824569702},{"id":"https://openalex.org/keywords/independent-and-identically-distributed-random-variables","display_name":"Independent and identically distributed random variables","score":0.43265557289123535},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4312629997730255},{"id":"https://openalex.org/keywords/inductive-bias","display_name":"Inductive bias","score":0.4231402575969696},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37283429503440857},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3443174958229065},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.31802600622177124},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.28547194600105286},{"id":"https://openalex.org/keywords/protein-structure","display_name":"Protein structure","score":0.22070619463920593},{"id":"https://openalex.org/keywords/protein-structure-prediction","display_name":"Protein structure prediction","score":0.21274909377098083},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1950366497039795},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.13795968890190125},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.10281488299369812},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.10068666934967041}],"concepts":[{"id":"https://openalex.org/C66153294","wikidata":"https://www.wikidata.org/wiki/Q899291","display_name":"CASP","level":4,"score":0.7630915641784668},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.638292670249939},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.6290347576141357},{"id":"https://openalex.org/C177877439","wikidata":"https://www.wikidata.org/wiki/Q7604413","display_name":"Statistical relational learning","level":3,"score":0.5649879574775696},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5088768005371094},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4807955324649811},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.4401801824569702},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.43265557289123535},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4312629997730255},{"id":"https://openalex.org/C197352929","wikidata":"https://www.wikidata.org/wiki/Q1074074","display_name":"Inductive bias","level":4,"score":0.4231402575969696},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37283429503440857},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3443174958229065},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31802600622177124},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.28547194600105286},{"id":"https://openalex.org/C47701112","wikidata":"https://www.wikidata.org/wiki/Q735188","display_name":"Protein structure","level":2,"score":0.22070619463920593},{"id":"https://openalex.org/C18051474","wikidata":"https://www.wikidata.org/wiki/Q899656","display_name":"Protein structure prediction","level":3,"score":0.21274909377098083},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1950366497039795},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.13795968890190125},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.10281488299369812},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.10068666934967041},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D008390","descriptor_name":"Markov Chains","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008390","descriptor_name":"Markov Chains","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008390","descriptor_name":"Markov Chains","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011487","descriptor_name":"Protein Conformation","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":"D011487","descriptor_name":"Protein Conformation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"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":"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}],"locations_count":5,"locations":[{"id":"doi:10.1093/bioinformatics/btp421","is_oa":false,"landing_page_url":"https://doi.org/10.1093/bioinformatics/btp421","pdf_url":null,"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:19592394","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/19592394","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},{"id":"pmh:oai:cris.unibo.it:11585/394758","is_oa":false,"landing_page_url":"http://hdl.handle.net/11585/394758","pdf_url":null,"source":{"id":"https://openalex.org/S4306402579","display_name":"Archivio istituzionale della ricerca (Alma Mater Studiorum Universit\u00e0 di Bologna)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210117483","host_organization_name":"Istituto di Ematologia di Bologna","host_organization_lineage":["https://openalex.org/I4210117483"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:flore.unifi.it:2158/373499","is_oa":false,"landing_page_url":"http://hdl.handle.net/2158/373499","pdf_url":null,"source":{"id":"https://openalex.org/S4306402033","display_name":"Florence Research (University of Florence)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45084792","host_organization_name":"University of Florence","host_organization_lineage":["https://openalex.org/I45084792"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:iris.unimore.it:11380/1122687","is_oa":true,"landing_page_url":"http://hdl.handle.net/11380/1122687","pdf_url":null,"source":{"id":"https://openalex.org/S4306400718","display_name":"IRIS UNIMORE (University of Modena and Reggio Emilia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I122346577","host_organization_name":"University of Modena and Reggio Emilia","host_organization_lineage":["https://openalex.org/I122346577"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:iris.unimore.it:11380/1122687","is_oa":true,"landing_page_url":"http://hdl.handle.net/11380/1122687","pdf_url":null,"source":{"id":"https://openalex.org/S4306400718","display_name":"IRIS UNIMORE (University of Modena and Reggio Emilia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I122346577","host_organization_name":"University of Modena and Reggio Emilia","host_organization_lineage":["https://openalex.org/I122346577"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[{"score":0.4399999976158142,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W121830907","https://openalex.org/W1568892534","https://openalex.org/W1585529040","https://openalex.org/W1604938182","https://openalex.org/W1964821516","https://openalex.org/W1977970897","https://openalex.org/W1985199442","https://openalex.org/W2008708467","https://openalex.org/W2028368848","https://openalex.org/W2033354942","https://openalex.org/W2042313354","https://openalex.org/W2042661033","https://openalex.org/W2076768638","https://openalex.org/W2096495474","https://openalex.org/W2100063856","https://openalex.org/W2113178668","https://openalex.org/W2136989186","https://openalex.org/W2137126099","https://openalex.org/W2149449280","https://openalex.org/W2157540858","https://openalex.org/W2158461363","https://openalex.org/W2158714788","https://openalex.org/W2159080219","https://openalex.org/W2164583490","https://openalex.org/W2912206496","https://openalex.org/W2994982620","https://openalex.org/W4256664446","https://openalex.org/W6634048602","https://openalex.org/W6683348493"],"related_works":["https://openalex.org/W2907502844","https://openalex.org/W3129034693","https://openalex.org/W2734531055","https://openalex.org/W3173151241","https://openalex.org/W2137126099","https://openalex.org/W2584568457","https://openalex.org/W4282813238","https://openalex.org/W1550614826","https://openalex.org/W1525804336","https://openalex.org/W2542311426"],"abstract_inverted_index":{"MOTIVATION:":[0],"Accurate":[1],"prediction":[2,14],"of":[3,15,19,67,79,106,170,180],"contacts":[4,60],"between":[5,93],"beta-strand":[6],"residues":[7],"can":[8,33],"significantly":[9,148,166],"contribute":[10],"towards":[11],"ab":[12],"initio":[13],"the":[16,24,43,56,97,168,181],"3D":[17],"structure":[18],"many":[20,66],"proteins.":[21],"Contacts":[22],"in":[23,109],"same":[25],"protein":[26],"are":[27,50,61,69,175,183],"highly":[28],"interdependent.":[29],"Therefore,":[30],"significant":[31],"improvements":[32],"be":[34],"expected":[35],"by":[36,104,158],"applying":[37],"statistical":[38,83],"relational":[39,84],"learners":[40],"that":[41,48,87],"overcome":[42],"usual":[44],"machine":[45],"learning":[46,85],"assumption":[47],"examples":[49],"independent":[51],"and":[52,95,123,143],"identically":[53],"distributed.":[54],"Furthermore,":[55],"dependencies":[57,92],"among":[58],"beta-residue":[59],"subject":[62],"to":[63,90,100],"strong":[64],"regularities,":[65],"which":[68,146,173],"known":[70],"a":[71,82,110,116,131],"priori.":[72],"In":[73],"this":[74],"article,":[75],"we":[76],"take":[77],"advantage":[78],"Markov":[80,124],"logic,":[81],"framework":[86],"is":[88,147],"able":[89],"capture":[91],"contacts,":[94],"constrain":[96],"solution":[98],"according":[99],"domain":[101],"knowledge":[102],"expressed":[103],"means":[105],"weighted":[107],"rules":[108],"logical":[111],"language.":[112],"RESULTS:":[113],"We":[114],"introduce":[115],"novel":[117],"hybrid":[118],"architecture":[119],"based":[120],"on":[121,189,199],"neural":[122,161],"logic":[125],"networks":[126],"with":[127,140,185],"grounding-specific":[128],"weights.":[129],"On":[130],"non-redundant":[132],"dataset,":[133],"our":[134],"method":[135],"achieves":[136],"44.9%":[137],"F(1)":[138,186],"measure,":[139],"47.3%":[141],"precision":[142],"42.7%":[144],"recall,":[145],"better":[149],"(P":[150],"<":[151],"0.01)":[152],"than":[153],"previously":[154],"reported":[155],"performance":[156],"obtained":[157],"2D":[159],"recursive":[160],"networks.":[162],"Our":[163],"approach":[164],"also":[165,193],"improves":[167],"number":[169],"chains":[171,182],"for":[172],"beta-strands":[174],"nearly":[176],"perfectly":[177],"paired":[178],"(36%":[179],"predicted":[184],">or=":[187],"70%":[188],"coarse":[190],"map).":[191],"It":[192],"outperforms":[194],"more":[195],"general":[196],"contact":[197],"predictors":[198],"recent":[200],"CASP":[201],"2008":[202],"targets.":[203]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":4}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2016-06-24T00:00:00"}
