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Much work has focused on parameter inference of stochastic and ordinary differential equation models using Approximate Bayesian Computation (ABC). While there is some recent work on inference in spatial models, this remains an open problem. Simultaneously, advances in topological data analysis (TDA), a field of computational mathematics, have enabled spatial patterns in data to be characterized.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Here, we focus on recent work using TDA to study different regimes of parameter space for a well-studied model of angiogenesis. We propose a method for combining TDA with ABC to infer parameters in the Anderson\u2013Chaplain model of angiogenesis. We demonstrate that this topological approach outperforms ABC approaches that use simpler statistics based on spatial features of the data. This is a first step toward a general framework of spatial parameter inference for biological systems, for which there may be a variety of filtrations, vectorizations and summary statistics to be considered.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>All code used to produce our results is available as a Snakemake workflow from github.com\/tt104\/tabc_angio.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac118","type":"journal-article","created":{"date-parts":[[2022,2,18]],"date-time":"2022-02-18T20:11:43Z","timestamp":1645215103000},"page":"2529-2535","source":"Crossref","is-referenced-by-count":11,"title":["Topological approximate Bayesian computation for parameter inference of an angiogenesis model"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7396-5116","authenticated-orcid":false,"given":"Thomas","family":"Thorne","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Surrey , Guildford GU2 7XH, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5931-7489","authenticated-orcid":false,"given":"Paul D W","family":"Kirk","sequence":"additional","affiliation":[{"name":"MRC Biostatistics Unit, University of Cambridge , Cambridge CB2 0SR, UK"},{"name":"Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), University of Cambridge , Cambridge CB2 0AW, UK"},{"name":"Cancer Research UK Cambridge Centre, Ovarian Cancer Programme , Cambridge CB2 0RE, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1705-7869","authenticated-orcid":false,"given":"Heather A","family":"Harrington","sequence":"additional","affiliation":[{"name":"Mathematical Institute, University of Oxford , Oxford OX2 6GG, UK"},{"name":"Wellcome Centre for Human Genetics, University of Oxford , Oxford OX3 7BN, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2022,2,22]]},"reference":[{"key":"2023041402545847400_","first-page":"1","article-title":"Persistence images: a stable vector representation of persistent homology","volume":"18","author":"Adams","year":"2017","journal-title":"J. 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