{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T16:10:49Z","timestamp":1758816649672,"version":"3.37.3"},"reference-count":15,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T00:00:00Z","timestamp":1602460800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Helmholtz School for Data Science in Life, Earth and Energy"},{"name":"Helmholtz Association of German Research Centres"},{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","award":["ERA-IB-14-81"],"award-info":[{"award-number":["ERA-IB-14-81"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,7,19]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Summary<\/jats:title>\n                  <jats:p>The C++ library Highly Optimized Polytope Sampling (HOPS) provides implementations of efficient and scalable algorithms for sampling convex-constrained models that are equipped with arbitrary target functions. For uniform sampling, substantial performance gains were achieved compared to the state-of-the-art. The ease of integration and utility of non-uniform sampling is showcased in a Bayesian inference setting, demonstrating how HOPS interoperates with third-party software.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>Source code is available at https:\/\/github.com\/modsim\/hops\/, tested on Linux and MS Windows, includes unit tests, detailed documentation, example applications and a Dockerfile.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaa872","type":"journal-article","created":{"date-parts":[[2020,9,24]],"date-time":"2020-09-24T19:20:38Z","timestamp":1600975238000},"page":"1776-1777","source":"Crossref","is-referenced-by-count":14,"title":["HOPS: high-performance library for (non-)uniform sampling of convex-constrained models"],"prefix":"10.1093","volume":"37","author":[{"given":"Johann F","family":"Jadebeck","sequence":"first","affiliation":[{"name":"Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum J\u00fclich GmbH , 52425 J\u00fclich, Germany"},{"name":"Computational Systems Biotechnology (AVT.CSB), RWTH Aachen University , 52062 Aachen, Germany"}]},{"given":"Axel","family":"Theorell","sequence":"additional","affiliation":[{"name":"Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum J\u00fclich GmbH , 52425 J\u00fclich, Germany"}]},{"given":"Samuel","family":"Leweke","sequence":"additional","affiliation":[{"name":"Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum J\u00fclich GmbH , 52425 J\u00fclich, Germany"}]},{"given":"Katharina","family":"N\u00f6h","sequence":"additional","affiliation":[{"name":"Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum J\u00fclich GmbH , 52425 J\u00fclich, Germany"}]}],"member":"286","published-online":{"date-parts":[[2020,10,12]]},"reference":[{"key":"2023051709460029100_btaa872-B1","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1287\/moor.18.2.255","article-title":"Hit-and-run algorithms for generating multivariate distributions","volume":"18","author":"B\u00e9lisle","year":"1993","journal-title":"Math. 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