{"id":"https://openalex.org/W2026625220","doi":"https://doi.org/10.1007/s10994-008-5086-2","title":"Graph kernels based on tree patterns for molecules","display_name":"Graph kernels based on tree patterns for molecules","publication_year":2008,"publication_date":"2008-10-03","ids":{"openalex":"https://openalex.org/W2026625220","doi":"https://doi.org/10.1007/s10994-008-5086-2","mag":"2026625220"},"language":"en","primary_location":{"id":"doi:10.1007/s10994-008-5086-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-008-5086-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-008-5086-2.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10994-008-5086-2.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015231461","display_name":"Pierre Mah\u00e9","orcid":"https://orcid.org/0000-0002-3173-6614"},"institutions":[{"id":"https://openalex.org/I70768539","display_name":"\u00c9cole Nationale Sup\u00e9rieure des Mines de Paris","ror":"https://ror.org/04y8cs423","country_code":"FR","type":"education","lineage":["https://openalex.org/I190752583","https://openalex.org/I2746051580","https://openalex.org/I70768539"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Pierre Mah\u00e9","raw_affiliation_strings":["Centre for Computational Biology, Ecole des Mines de Paris\u2014ParisTech, 35 rue Saint Honor\u00e9, 77305, Fontainebleau, France"],"affiliations":[{"raw_affiliation_string":"Centre for Computational Biology, Ecole des Mines de Paris\u2014ParisTech, 35 rue Saint Honor\u00e9, 77305, Fontainebleau, France","institution_ids":["https://openalex.org/I70768539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064770739","display_name":"Jean\u2010Philippe Vert","orcid":"https://orcid.org/0000-0001-9510-8441"},"institutions":[{"id":"https://openalex.org/I154526488","display_name":"Inserm","ror":"https://ror.org/02vjkv261","country_code":"FR","type":"funder","lineage":["https://openalex.org/I154526488"]},{"id":"https://openalex.org/I70768539","display_name":"\u00c9cole Nationale Sup\u00e9rieure des Mines de Paris","ror":"https://ror.org/04y8cs423","country_code":"FR","type":"education","lineage":["https://openalex.org/I190752583","https://openalex.org/I2746051580","https://openalex.org/I70768539"]},{"id":"https://openalex.org/I80043","display_name":"Institut Curie","ror":"https://ror.org/04t0gwh46","country_code":"FR","type":"funder","lineage":["https://openalex.org/I80043"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jean-Philippe Vert","raw_affiliation_strings":["Centre for Computational Biology, Ecole des Mines de Paris\u2014ParisTech, 35 rue Saint Honor\u00e9, 77305, Fontainebleau, France","INSERM, U900, 75248, Paris, France","Institut Curie, 75248, Paris, France"],"affiliations":[{"raw_affiliation_string":"Centre for Computational Biology, Ecole des Mines de Paris\u2014ParisTech, 35 rue Saint Honor\u00e9, 77305, Fontainebleau, France","institution_ids":["https://openalex.org/I70768539"]},{"raw_affiliation_string":"INSERM, U900, 75248, Paris, France","institution_ids":["https://openalex.org/I154526488"]},{"raw_affiliation_string":"Institut Curie, 75248, Paris, France","institution_ids":["https://openalex.org/I80043"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5015231461"],"corresponding_institution_ids":["https://openalex.org/I70768539"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":13.9727,"has_fulltext":true,"cited_by_count":209,"citation_normalized_percentile":{"value":0.99140285,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"75","issue":"1","first_page":"3","last_page":"35"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T10908","display_name":"Analytical Chemistry and Chromatography","score":0.9840999841690063,"subfield":{"id":"https://openalex.org/subfields/1607","display_name":"Spectroscopy"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9735000133514404,"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/graph-kernel","display_name":"Graph kernel","score":0.576438844203949},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5123406648635864},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.47806814312934875},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46881866455078125},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.45742735266685486},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4537525177001953},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.44864872097969055},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4352152645587921},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4073018729686737},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3561161756515503},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.316371351480484},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2988729476928711},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.2962365746498108},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.29539427161216736},{"id":"https://openalex.org/keywords/polynomial-kernel","display_name":"Polynomial kernel","score":0.18554189801216125}],"concepts":[{"id":"https://openalex.org/C100595998","wikidata":"https://www.wikidata.org/wiki/Q11731931","display_name":"Graph kernel","level":5,"score":0.576438844203949},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5123406648635864},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.47806814312934875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46881866455078125},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.45742735266685486},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4537525177001953},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.44864872097969055},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4352152645587921},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4073018729686737},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3561161756515503},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.316371351480484},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2988729476928711},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.2962365746498108},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.29539427161216736},{"id":"https://openalex.org/C160446489","wikidata":"https://www.wikidata.org/wiki/Q7226642","display_name":"Polynomial kernel","level":4,"score":0.18554189801216125}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s10994-008-5086-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-008-5086-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-008-5086-2.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.493.4179","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.493.4179","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://hal.archives-ouvertes.fr/docs/00/09/54/88/PDF/techreport.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.1007/s10994-008-5086-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-008-5086-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-008-5086-2.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.6200000047683716,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2026625220.pdf","grobid_xml":"https://content.openalex.org/works/W2026625220.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W49486804","https://openalex.org/W1510073064","https://openalex.org/W1531524766","https://openalex.org/W1560724230","https://openalex.org/W1592376869","https://openalex.org/W1816257748","https://openalex.org/W2017091502","https://openalex.org/W2018590585","https://openalex.org/W2020816856","https://openalex.org/W2039444222","https://openalex.org/W2053080554","https://openalex.org/W2073175807","https://openalex.org/W2081301924","https://openalex.org/W2098689079","https://openalex.org/W2099438806","https://openalex.org/W2137262074","https://openalex.org/W2153037537","https://openalex.org/W2153635508","https://openalex.org/W2161723275","https://openalex.org/W2215622313","https://openalex.org/W2419658023","https://openalex.org/W2492427238","https://openalex.org/W2527497076","https://openalex.org/W3120421331","https://openalex.org/W3144619878","https://openalex.org/W6631775758","https://openalex.org/W6727823310"],"related_works":["https://openalex.org/W2574115973","https://openalex.org/W3100948281","https://openalex.org/W1983263273","https://openalex.org/W2828181497","https://openalex.org/W2179275589","https://openalex.org/W1558903433","https://openalex.org/W2096302783","https://openalex.org/W2161416301","https://openalex.org/W2189183545","https://openalex.org/W2093878082"],"abstract_inverted_index":{"Motivated":[0],"by":[1,25],"chemical":[2],"applications,":[3],"we":[4],"revisit":[5],"and":[6,27,39,86,122,143],"extend":[7],"a":[8,49],"family":[9],"of":[10,20,30,55,79,92,115,141],"positive":[11],"definite":[12],"kernels":[13,47,74,87,138],"for":[14,147],"graphs":[15],"based":[16,75],"on":[17,35,76,82,96,139],"the":[18,31,53,56,63,77,83,90,97,113,119,123,130],"detection":[19,91],"common":[21,80,94],"subtrees,":[22,95],"initially":[23],"proposed":[24],"Ramon":[26],"G\u00e4rtner":[28],"(Proceedings":[29],"first":[32,110],"international":[33],"workshop":[34],"mining":[36],"graphs,":[37],"trees":[38],"sequences,":[40],"pp.":[41],"65\u201374,":[42],"2003).":[43],"We":[44,100,133],"propose":[45,102],"new":[46,137],"with":[48,150],"parameter":[50,66],"to":[51,61,68,106],"control":[52],"complexity":[54],"subtrees":[57,116],"used":[58],"as":[59],"features":[60,128],"represent":[62],"graphs.":[64],"This":[65],"allows":[67],"smoothly":[69],"interpolate":[70],"between":[71],"classical":[72],"graph":[73,131],"count":[78],"walks,":[81],"one":[84,125],"hand,":[85],"that":[88,117],"emphasize":[89],"large":[93],"other":[98],"hand.":[99],"also":[101],"two":[103],"modular":[104],"extensions":[105],"this":[107],"formulation.":[108],"The":[109],"extension":[111],"increases":[112],"number":[114],"define":[118],"feature":[120],"space,":[121],"second":[124],"removes":[126],"noisy":[127],"from":[129],"representations.":[132],"validate":[134],"experimentally":[135],"these":[136],"problems":[140],"toxicity":[142],"anti-cancer":[144],"activity":[145],"prediction":[146],"small":[148],"molecules":[149],"support":[151],"vector":[152],"machines.":[153]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":12},{"year":2017,"cited_by_count":17},{"year":2016,"cited_by_count":14},{"year":2015,"cited_by_count":16},{"year":2014,"cited_by_count":23},{"year":2013,"cited_by_count":23},{"year":2012,"cited_by_count":17}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
