{"id":"https://openalex.org/W2424046091","doi":"https://doi.org/10.1007/s11222-016-9668-8","title":"Approximate Bayesian inference in semi-mechanistic models","display_name":"Approximate Bayesian inference in semi-mechanistic models","publication_year":2016,"publication_date":"2016-06-16","ids":{"openalex":"https://openalex.org/W2424046091","doi":"https://doi.org/10.1007/s11222-016-9668-8","mag":"2424046091","pmid":"https://pubmed.ncbi.nlm.nih.gov/32226236"},"language":"en","primary_location":{"id":"doi:10.1007/s11222-016-9668-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-016-9668-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-016-9668-8.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11222-016-9668-8.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074697189","display_name":"Andrej Aderhold","orcid":"https://orcid.org/0000-0003-0197-5339"},"institutions":[{"id":"https://openalex.org/I7882870","display_name":"University of Glasgow","ror":"https://ror.org/00vtgdb53","country_code":"GB","type":"education","lineage":["https://openalex.org/I7882870"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Andrej Aderhold","raw_affiliation_strings":["1School of Mathematics and Statistics, Glasgow University, Glasgow, UK","School of Mathematics and Statistics, Glasgow University, Glasgow, UK"],"affiliations":[{"raw_affiliation_string":"1School of Mathematics and Statistics, Glasgow University, Glasgow, UK","institution_ids":[]},{"raw_affiliation_string":"School of Mathematics and Statistics, Glasgow University, Glasgow, UK","institution_ids":["https://openalex.org/I7882870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080836461","display_name":"Dirk Husmeier","orcid":"https://orcid.org/0000-0003-1673-7413"},"institutions":[{"id":"https://openalex.org/I7882870","display_name":"University of Glasgow","ror":"https://ror.org/00vtgdb53","country_code":"GB","type":"education","lineage":["https://openalex.org/I7882870"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Dirk Husmeier","raw_affiliation_strings":["1School of Mathematics and Statistics, Glasgow University, Glasgow, UK","School of Mathematics and Statistics, Glasgow University, Glasgow, UK"],"affiliations":[{"raw_affiliation_string":"1School of Mathematics and Statistics, Glasgow University, Glasgow, UK","institution_ids":[]},{"raw_affiliation_string":"School of Mathematics and Statistics, Glasgow University, Glasgow, UK","institution_ids":["https://openalex.org/I7882870"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103139038","display_name":"Marco Grzegorczyk","orcid":"https://orcid.org/0000-0001-6884-5892"},"institutions":[{"id":"https://openalex.org/I169381384","display_name":"University of Groningen","ror":"https://ror.org/012p63287","country_code":"NL","type":"education","lineage":["https://openalex.org/I169381384"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Marco Grzegorczyk","raw_affiliation_strings":["2Johann Bernoulli Institute (JBI), Groningen University, Groningen, The Netherlands","Johann Bernoulli Institute (JBI), Groningen University, Groningen, The Netherlands"],"affiliations":[{"raw_affiliation_string":"2Johann Bernoulli Institute (JBI), Groningen University, Groningen, The Netherlands","institution_ids":[]},{"raw_affiliation_string":"Johann Bernoulli Institute (JBI), Groningen University, Groningen, The Netherlands","institution_ids":["https://openalex.org/I169381384"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103139038"],"corresponding_institution_ids":["https://openalex.org/I169381384"],"apc_list":{"value":2090,"currency":"EUR","value_usd":2690},"apc_paid":{"value":2090,"currency":"EUR","value_usd":2690},"fwci":2.0919,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.87103231,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"27","issue":"4","first_page":"1003","last_page":"1040"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10621","display_name":"Gene Regulatory Network Analysis","score":0.9962999820709229,"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/T10621","display_name":"Gene Regulatory Network Analysis","score":0.9962999820709229,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10044","display_name":"Protein Structure and Dynamics","score":0.9933000206947327,"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/computer-science","display_name":"Computer science","score":0.6738977432250977},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6601499319076538},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5273488759994507},{"id":"https://openalex.org/keywords/bayes-factor","display_name":"Bayes factor","score":0.4845127463340759},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.47482284903526306},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.474008172750473},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.4660072922706604},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.463566392660141},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45130831003189087},{"id":"https://openalex.org/keywords/frequentist-inference","display_name":"Frequentist inference","score":0.44350746273994446},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.43417850136756897},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4324132800102234},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.4260900020599365},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36514580249786377},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25301671028137207},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13094976544380188}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6738977432250977},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6601499319076538},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5273488759994507},{"id":"https://openalex.org/C142291917","wikidata":"https://www.wikidata.org/wiki/Q4165283","display_name":"Bayes factor","level":4,"score":0.4845127463340759},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.47482284903526306},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.474008172750473},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.4660072922706604},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.463566392660141},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45130831003189087},{"id":"https://openalex.org/C162376815","wikidata":"https://www.wikidata.org/wiki/Q2158281","display_name":"Frequentist inference","level":4,"score":0.44350746273994446},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.43417850136756897},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4324132800102234},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.4260900020599365},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36514580249786377},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25301671028137207},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13094976544380188}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1007/s11222-016-9668-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-016-9668-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-016-9668-8.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},{"id":"pmid:32226236","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32226236","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":"Statistics and computing","raw_type":null},{"id":"pmh:oai:pure.rug.nl:openaire/67ff007b-0e93-4d4a-b7aa-414ebb126d43","is_oa":true,"landing_page_url":"https://research.rug.nl/en/publications/67ff007b-0e93-4d4a-b7aa-414ebb126d43","pdf_url":null,"source":{"id":"https://openalex.org/S4306400420","display_name":"University of Groningen research database (University of Groningen / Centre for Information Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I169381384","host_organization_name":"University of Groningen","host_organization_lineage":["https://openalex.org/I169381384"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Aderhold, A, Husmeier, D & Grzegorczyk, M 2017, 'Approximate Bayesian inference in semi-mechanistic models', Statistics and Computing, vol. 27, no. 4, pp. 1003-1040. https://doi.org/10.1007/s11222-016-9668-8","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:eprints.gla.ac.uk:120872","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4210235606","display_name":"ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam)","issn_l":"2622-8912","issn":["2622-8912","2622-8920"],"is_oa":false,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Articles"},{"id":"pmh:oai:pure.rug.nl:publications/67ff007b-0e93-4d4a-b7aa-414ebb126d43","is_oa":true,"landing_page_url":"https://hdl.handle.net/11370/67ff007b-0e93-4d4a-b7aa-414ebb126d43","pdf_url":"https://pure.rug.nl/ws/files/64556698/Aderhold2017_Article_ApproximateBayesianInferenceIn.pdf","source":{"id":"https://openalex.org/S4306400420","display_name":"University of Groningen research database (University of Groningen / Centre for Information Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I169381384","host_organization_name":"University of Groningen","host_organization_lineage":["https://openalex.org/I169381384"],"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":"Aderhold, A, Husmeier, D & Grzegorczyk, M 2017, 'Approximate Bayesian inference in semi-mechanistic models', Statistics and Computing, vol. 27, no. 4, pp. 1003-1040. https://doi.org/10.1007/s11222-016-9668-8","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pubmedcentral.nih.gov:7089672","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7089672","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Stat Comput","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1007/s11222-016-9668-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-016-9668-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-016-9668-8.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1190157208","display_name":null,"funder_award_id":"EP/L020319/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G1614786199","display_name":null,"funder_award_id":"245143","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G1934935867","display_name":null,"funder_award_id":"Engineering and Physical Sciences R","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G3071701163","display_name":"Computational inference of biopathway dynamics and structures","funder_award_id":"EP/L020319/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2424046091.pdf","grobid_xml":"https://content.openalex.org/works/W2424046091.grobid-xml"},"referenced_works_count":60,"referenced_works":["https://openalex.org/W136174036","https://openalex.org/W1503398984","https://openalex.org/W1550570395","https://openalex.org/W1558471429","https://openalex.org/W1575978816","https://openalex.org/W1602551265","https://openalex.org/W1681969670","https://openalex.org/W1746819321","https://openalex.org/W1788054578","https://openalex.org/W1969682141","https://openalex.org/W1975971707","https://openalex.org/W1976526581","https://openalex.org/W1976742127","https://openalex.org/W1983030487","https://openalex.org/W1983350265","https://openalex.org/W1991363773","https://openalex.org/W1997582420","https://openalex.org/W2008205728","https://openalex.org/W2008756354","https://openalex.org/W2017470450","https://openalex.org/W2021310666","https://openalex.org/W2045656233","https://openalex.org/W2057765075","https://openalex.org/W2058221907","https://openalex.org/W2060512257","https://openalex.org/W2071818961","https://openalex.org/W2080679139","https://openalex.org/W2081409037","https://openalex.org/W2096954258","https://openalex.org/W2098626000","https://openalex.org/W2109384743","https://openalex.org/W2117076645","https://openalex.org/W2118671962","https://openalex.org/W2122966123","https://openalex.org/W2123222757","https://openalex.org/W2123986939","https://openalex.org/W2124790653","https://openalex.org/W2130902307","https://openalex.org/W2142631293","https://openalex.org/W2148534890","https://openalex.org/W2149656802","https://openalex.org/W2152246075","https://openalex.org/W2155418451","https://openalex.org/W2156444576","https://openalex.org/W2157479132","https://openalex.org/W2157825442","https://openalex.org/W2158128575","https://openalex.org/W2160624840","https://openalex.org/W2166303358","https://openalex.org/W2169264416","https://openalex.org/W2184489869","https://openalex.org/W2218277484","https://openalex.org/W2787027754","https://openalex.org/W2950059309","https://openalex.org/W3103263318","https://openalex.org/W3108109080","https://openalex.org/W4211049957","https://openalex.org/W4243634280","https://openalex.org/W4248681815","https://openalex.org/W4254014359"],"related_works":["https://openalex.org/W4309301408","https://openalex.org/W4297513322","https://openalex.org/W4287210717","https://openalex.org/W2991615686","https://openalex.org/W3103377301","https://openalex.org/W2478683457","https://openalex.org/W3153031932","https://openalex.org/W4294769481","https://openalex.org/W4221107656","https://openalex.org/W1489016866"],"abstract_inverted_index":{"Inference":[0],"of":[1,7,67,75],"interaction":[2],"networks":[3],"represented":[4],"by":[5],"systems":[6],"differential":[8],"equations":[9],"is":[10],"a":[11,24,99],"challenging":[12],"problem":[13],"in":[14],"many":[15],"scientific":[16],"disciplines.":[17],"In":[18],"the":[19,34,41,65,73,95],"present":[20],"article,":[21],"we":[22,71],"follow":[23],"semi-mechanistic":[25],"modelling":[26],"approach":[27],"based":[28],"on":[29],"gradient":[30],"matching.":[31],"We":[32,55,93],"investigate":[33],"extent":[35],"to":[36],"which":[37],"key":[38],"factors,":[39],"including":[40,79],"kinetic":[42],"model,":[43],"statistical":[44],"formulation":[45],"and":[46,70,85],"numerical":[47,87],"methods,":[48],"impact":[49],"upon":[50],"performance":[51],"at":[52],"network":[53],"reconstruction.":[54],"emphasize":[56],"general":[57],"lessons":[58],"for":[59,89],"computational":[60],"statisticians":[61],"when":[62],"faced":[63],"with":[64,98],"challenge":[66],"model":[68],"selection,":[69],"assess":[72],"accuracy":[74],"various":[76],"alternative":[77],"paradigms,":[78],"recent":[80],"widely":[81],"applicable":[82],"information":[83],"criteria":[84],"different":[86],"procedures":[88],"approximating":[90],"Bayes":[91],"factors.":[92],"conduct":[94],"comparative":[96],"evaluation":[97],"novel":[100],"inferential":[101],"pipeline":[102],"that":[103],"systematically":[104],"disambiguates":[105],"confounding":[106],"factors":[107],"via":[108],"an":[109],"ANOVA":[110],"scheme.":[111]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
