{"id":"https://openalex.org/W4408248844","doi":"https://doi.org/10.1007/s00180-025-01606-5","title":"Approximate Bayesian inference in a model for self-generated gradient collective cell movement","display_name":"Approximate Bayesian inference in a model for self-generated gradient collective cell movement","publication_year":2025,"publication_date":"2025-03-08","ids":{"openalex":"https://openalex.org/W4408248844","doi":"https://doi.org/10.1007/s00180-025-01606-5","pmid":"https://pubmed.ncbi.nlm.nih.gov/40661154"},"language":"en","primary_location":{"id":"doi:10.1007/s00180-025-01606-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00180-025-01606-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00180-025-01606-5.pdf","source":{"id":"https://openalex.org/S8500805","display_name":"Computational Statistics","issn_l":"0943-4062","issn":["0943-4062","1613-9658"],"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":"Computational Statistics","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/s00180-025-01606-5.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jon Devlin","orcid":null},"institutions":[{"id":"https://openalex.org/I181647926","display_name":"University of Strathclyde","ror":"https://ror.org/00n3w3b69","country_code":"GB","type":"education","lineage":["https://openalex.org/I181647926"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jon Devlin","raw_affiliation_strings":["Department of Mathematics and Statistics, University of Strathclyde, Glasgow, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, University of Strathclyde, Glasgow, UK","institution_ids":["https://openalex.org/I181647926"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056361618","display_name":"Agnieszka Borowska","orcid":"https://orcid.org/0000-0001-9123-6227"},"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":"Agnieszka Borowska","raw_affiliation_strings":["School of Mathematics and Statistics, University of Glasgow, Glasgow, UK"],"raw_orcid":"https://orcid.org/0000-0001-9123-6227","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, University of Glasgow, 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":["School of Mathematics and Statistics, University of Glasgow, Glasgow, UK"],"raw_orcid":"https://orcid.org/0000-0003-1673-7413","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, University of Glasgow, Glasgow, UK","institution_ids":["https://openalex.org/I7882870"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045486287","display_name":"J.A. Mackenzie","orcid":"https://orcid.org/0000-0003-4412-7057"},"institutions":[{"id":"https://openalex.org/I181647926","display_name":"University of Strathclyde","ror":"https://ror.org/00n3w3b69","country_code":"GB","type":"education","lineage":["https://openalex.org/I181647926"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"John Mackenzie","raw_affiliation_strings":["Department of Mathematics and Statistics, University of Strathclyde, Glasgow, UK"],"raw_orcid":"https://orcid.org/0000-0003-4412-7057","affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, University of Strathclyde, Glasgow, UK","institution_ids":["https://openalex.org/I181647926"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5045486287"],"corresponding_institution_ids":["https://openalex.org/I181647926"],"apc_list":{"value":2490,"currency":"EUR","value_usd":3090},"apc_paid":{"value":2490,"currency":"EUR","value_usd":3090},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04443531,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"7","first_page":"3399","last_page":"3452"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11829","display_name":"Mathematical Biology Tumor Growth","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/2611","display_name":"Modeling and Simulation"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9926000237464905,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/approximate-bayesian-computation","display_name":"Approximate Bayesian computation","score":0.7588269710540771},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6585526466369629},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5647258758544922},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4627295732498169},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.444315642118454},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.4381406605243683},{"id":"https://openalex.org/keywords/stochastic-differential-equation","display_name":"Stochastic differential equation","score":0.43391892313957214},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.432967871427536},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.41797035932540894},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.4101818799972534},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3913307785987854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37529587745666504},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.29010432958602905},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27830296754837036}],"concepts":[{"id":"https://openalex.org/C2779377595","wikidata":"https://www.wikidata.org/wiki/Q21045424","display_name":"Approximate Bayesian computation","level":3,"score":0.7588269710540771},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6585526466369629},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5647258758544922},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4627295732498169},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.444315642118454},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4381406605243683},{"id":"https://openalex.org/C51955184","wikidata":"https://www.wikidata.org/wiki/Q1545585","display_name":"Stochastic differential equation","level":2,"score":0.43391892313957214},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.432967871427536},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.41797035932540894},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.4101818799972534},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3913307785987854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37529587745666504},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.29010432958602905},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27830296754837036},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.0}],"mesh":[],"locations_count":7,"locations":[{"id":"doi:10.1007/s00180-025-01606-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00180-025-01606-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00180-025-01606-5.pdf","source":{"id":"https://openalex.org/S8500805","display_name":"Computational Statistics","issn_l":"0943-4062","issn":["0943-4062","1613-9658"],"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":"Computational Statistics","raw_type":"journal-article"},{"id":"pmid:40661154","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40661154","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":"Computational statistics","raw_type":null},{"id":"pmh:oai:research.vu.nl:openaire/419a11a6-034c-4016-8901-725095bb8e1e","is_oa":true,"landing_page_url":"https://research.vu.nl/en/publications/419a11a6-034c-4016-8901-725095bb8e1e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401107","display_name":"VU Research Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I865915315","host_organization_name":"Vrije Universiteit Amsterdam","host_organization_lineage":["https://openalex.org/I865915315"],"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":"Devlin, J, Borowska, A, Husmeier, D & Mackenzie, J 2025, 'Approximate Bayesian inference in a model for self-generated gradient collective cell movement', Computational Statistics, vol. 40, no. 7, pp. 3399-3452. https://doi.org/10.1007/s00180-025-01606-5","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:eprints.gla.ac.uk:349339","is_oa":true,"landing_page_url":"https://eprints.gla.ac.uk/view/author/46438.html>","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":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Articles"},{"id":"pmh:oai:pubmedcentral.nih.gov:12255578","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12255578","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12255578/pdf/180_2025_Article_1606.pdf","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":"Comput Stat","raw_type":"Text"},{"id":"pmh:oai:strathprints.strath.ac.uk:92087","is_oa":true,"landing_page_url":"https://strathprints.strath.ac.uk/view/author/800049.html>","pdf_url":"https://strathprints.strath.ac.uk/92087/13/Devlin-etal-CS-2025-Approximate-Bayesian-inference-in-a-model-for-self-generated.pdf","source":{"id":"https://openalex.org/S4306402226","display_name":"Strathprints: The University of Strathclyde institutional repository (University of Strathclyde)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I181647926","host_organization_name":"University of Strathclyde","host_organization_lineage":["https://openalex.org/I181647926"],"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":"Article"},{"id":"pmh:oai:research.vu.nl:publications/419a11a6-034c-4016-8901-725095bb8e1e","is_oa":true,"landing_page_url":"https://hdl.handle.net/1871.1/419a11a6-034c-4016-8901-725095bb8e1e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401107","display_name":"VU Research Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I865915315","host_organization_name":"Vrije Universiteit Amsterdam","host_organization_lineage":["https://openalex.org/I865915315"],"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":"Devlin, J, Borowska, A, Husmeier, D & Mackenzie, J 2025, 'Approximate Bayesian inference in a model for self-generated gradient collective cell movement', Computational Statistics, vol. 40, no. 7, pp. 3399-3452. https://doi.org/10.1007/s00180-025-01606-5","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s00180-025-01606-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00180-025-01606-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00180-025-01606-5.pdf","source":{"id":"https://openalex.org/S8500805","display_name":"Computational Statistics","issn_l":"0943-4062","issn":["0943-4062","1613-9658"],"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":"Computational Statistics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3750727421","display_name":null,"funder_award_id":"C22713/A21462","funder_id":"https://openalex.org/F4320319985","funder_display_name":"Cancer Research UK"},{"id":"https://openalex.org/G5187265158","display_name":"Closed-Loop Data Science for Complex, Computationally- and Data-Intensive Analytics","funder_award_id":"EP/R018634/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G5572079770","display_name":"EPSRC Centre for Multiscale Soft Tissue Mechanics - with application to heart & cancer","funder_award_id":"EP/N014642/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G7678486561","display_name":null,"funder_award_id":"EP/N014642","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G8346705295","display_name":"The SofTMech Statistical Emulation and Translation Hub","funder_award_id":"EP/T017899/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G8352026019","display_name":null,"funder_award_id":"R018634/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320319985","display_name":"Cancer Research UK","ror":"https://ror.org/054225q67"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4408248844.pdf"},"referenced_works_count":74,"referenced_works":["https://openalex.org/W1594863551","https://openalex.org/W1771360046","https://openalex.org/W1793259860","https://openalex.org/W1836016492","https://openalex.org/W1967288931","https://openalex.org/W1968970043","https://openalex.org/W1980875771","https://openalex.org/W1981920009","https://openalex.org/W1986490461","https://openalex.org/W1987347396","https://openalex.org/W1993356393","https://openalex.org/W2005088757","https://openalex.org/W2009894386","https://openalex.org/W2025909913","https://openalex.org/W2026039411","https://openalex.org/W2034795216","https://openalex.org/W2044278781","https://openalex.org/W2048987027","https://openalex.org/W2054625522","https://openalex.org/W2054821964","https://openalex.org/W2057298293","https://openalex.org/W2060016742","https://openalex.org/W2067392831","https://openalex.org/W2068499405","https://openalex.org/W2071867803","https://openalex.org/W2089657469","https://openalex.org/W2092124742","https://openalex.org/W2093889759","https://openalex.org/W2103660236","https://openalex.org/W2112794562","https://openalex.org/W2113520457","https://openalex.org/W2116416291","https://openalex.org/W2117238111","https://openalex.org/W2118661871","https://openalex.org/W2119261959","https://openalex.org/W2127281696","https://openalex.org/W2139288598","https://openalex.org/W2145287259","https://openalex.org/W2147688960","https://openalex.org/W2151729750","https://openalex.org/W2152246075","https://openalex.org/W2152523443","https://openalex.org/W2155162055","https://openalex.org/W2162288469","https://openalex.org/W2167030304","https://openalex.org/W2167158173","https://openalex.org/W2266526867","https://openalex.org/W2276651706","https://openalex.org/W2299806323","https://openalex.org/W2345070118","https://openalex.org/W2405505865","https://openalex.org/W2485609644","https://openalex.org/W2519192276","https://openalex.org/W2546121870","https://openalex.org/W2626930952","https://openalex.org/W2742111569","https://openalex.org/W2745090763","https://openalex.org/W2793152198","https://openalex.org/W2801069323","https://openalex.org/W2895152177","https://openalex.org/W2910559903","https://openalex.org/W2916041869","https://openalex.org/W2950361325","https://openalex.org/W2963284230","https://openalex.org/W2968619018","https://openalex.org/W2968787565","https://openalex.org/W2970108440","https://openalex.org/W2987732919","https://openalex.org/W3100322616","https://openalex.org/W3100893285","https://openalex.org/W3118577024","https://openalex.org/W3125654536","https://openalex.org/W4211049957","https://openalex.org/W4248681815"],"related_works":["https://openalex.org/W2964314781","https://openalex.org/W4389708677","https://openalex.org/W3006565005","https://openalex.org/W3122206612","https://openalex.org/W4287868071","https://openalex.org/W2611832276","https://openalex.org/W69468016","https://openalex.org/W2007093222","https://openalex.org/W4321613659","https://openalex.org/W2145178290"],"abstract_inverted_index":{"In":[0],"this":[1],"article":[2],"we":[3,41,107],"explore":[4],"parameter":[5],"inference":[6,37],"in":[7,21,195],"a":[8,17,24,31,98,109,117,196],"novel":[9],"hybrid":[10],"discrete-continuum":[11],"model":[12,29,168],"describing":[13],"the":[14,64,77,82,86,93,125,137,142,146,151,164,188],"movement":[15,167,182],"of":[16,19,88,127,191],"population":[18],"cells":[20],"response":[22],"to":[23,76,80,123,163,169,179],"self-generated":[25],"chemotactic":[26],"gradient.":[27],"The":[28,156],"employs":[30],"drift-diffusion":[32,111],"stochastic":[33,112],"process,":[34],"rendering":[35],"likelihood-based":[36],"methods":[38],"impractical.":[39],"Consequently,":[40],"consider":[42],"approximate":[43,81],"Bayesian":[44],"computation":[45],"(ABC)":[46],"methods,":[47,91],"which":[48],"have":[49],"gained":[50],"popularity":[51],"for":[52,97,145],"models":[53],"with":[54],"intractable":[55],"or":[56],"computationally":[57],"expensive":[58],"likelihoods.":[59],"ABC":[60,90,129,158,193],"involves":[61],"simulating":[62],"from":[63,69],"generative":[65],"model,":[66,149],"using":[67],"parameters":[68],"generated":[70],"observations":[71],"that":[72],"are":[73,160],"\"close":[74],"enough\"":[75],"true":[78],"data":[79],"posterior":[83,144,152],"distribution.":[84],"Given":[85],"plethora":[87],"existing":[89],"selecting":[92],"most":[94],"suitable":[95],"one":[96],"specific":[99],"problem":[100],"can":[101],"be":[102],"challenging.":[103],"To":[104],"address":[105],"this,":[106],"employ":[108],"simple":[110],"differential":[113],"equation":[114],"(SDE)":[115],"as":[116],"benchmark":[118],"problem.":[119],"This":[120,174],"allows":[121],"us":[122],"assess":[124],"accuracy":[126],"popular":[128],"algorithms":[130,159,194],"under":[131],"known":[132],"configurations.":[133],"We":[134],"also":[135,184],"evaluate":[136],"bias":[138],"between":[139],"ABC-posteriors":[140],"and":[141],"exact":[143],"basic":[147],"SDE":[148],"where":[150],"distribution":[153],"is":[154],"tractable.":[155],"top-performing":[157],"subsequently":[161],"applied":[162],"proposed":[165],"cell":[166,181],"infer":[170],"its":[171],"key":[172],"parameters.":[173],"study":[175],"not":[176],"only":[177],"contributes":[178],"understanding":[180],"but":[183],"sheds":[185],"light":[186],"on":[187],"comparative":[189],"efficiency":[190],"different":[192],"well-defined":[197],"context.":[198]},"counts_by_year":[],"updated_date":"2026-07-10T07:45:09.275182","created_date":"2025-10-10T00:00:00"}