{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,12]],"date-time":"2026-04-12T08:32:16Z","timestamp":1775982736297,"version":"3.50.1"},"reference-count":72,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2024,4,17]],"date-time":"2024-04-17T00:00:00Z","timestamp":1713312000000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Joachim Herz Stiftung Add-on Fellowship for Interdisciplinary Life Science"},{"DOI":"10.13039\/501100001656","name":"Helmholtz Association","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001656","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,5,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>In recent years, many algorithms for inferring gene regulatory networks from single-cell transcriptomic data have been published. Several studies have evaluated their accuracy in estimating the presence of an interaction between pairs of genes. However, these benchmarking analyses do not quantify the algorithms\u2019 ability to capture structural properties of networks, which are fundamental, e.g., for studying the robustness of a gene network to external perturbations. Here, we devise a three-step benchmarking pipeline called STREAMLINE that quantifies the ability of algorithms to capture topological properties of networks and identify hubs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>To this aim, we use data simulated from different types of networks as well as experimental data from three different organisms. We apply our benchmarking pipeline to four inference algorithms and provide guidance on which algorithm should be used depending on the global network property of interest.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>STREAMLINE is available at https:\/\/github.com\/ScialdoneLab\/STREAMLINE. The data generated in this study are available at https:\/\/doi.org\/10.5281\/zenodo.10710444.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btae267","type":"journal-article","created":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T22:53:45Z","timestamp":1713308025000},"source":"Crossref","is-referenced-by-count":8,"title":["Topological benchmarking of algorithms to infer gene regulatory networks from single-cell RNA-seq data"],"prefix":"10.1093","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9485-1217","authenticated-orcid":false,"given":"Marco","family":"Stock","sequence":"first","affiliation":[{"name":"Institute of Epigenetics and Stem Cells, Helmholtz Zentrum M\u00fcnchen\u2014German Research Center for Environmental Health , Munich 81377, Germany"},{"name":"Institute of Functional Epigenetics, Helmholtz Zentrum M\u00fcnchen\u2014German Research Center for Environmental Health , Munich 85764, Germany"},{"name":"Institute of Computational Biology, Helmholtz Zentrum M\u00fcnchen\u2014German Research Center for Environmental Health , Munich 85764, Germany"},{"name":"TUM School of Life Sciences Weihenstephan, Technical University of Munich , Munich 85354, Germany"}]},{"given":"Niclas","family":"Popp","sequence":"additional","affiliation":[{"name":"Institute of Epigenetics and Stem Cells, Helmholtz Zentrum M\u00fcnchen\u2014German Research Center for Environmental Health , Munich 81377, Germany"},{"name":"Institute of Functional Epigenetics, Helmholtz Zentrum M\u00fcnchen\u2014German Research Center for Environmental Health , Munich 85764, Germany"},{"name":"Institute of Computational Biology, Helmholtz Zentrum M\u00fcnchen\u2014German Research Center for Environmental Health , Munich 85764, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2096-3210","authenticated-orcid":false,"given":"Jonathan","family":"Fiorentino","sequence":"additional","affiliation":[{"name":"Institute of Epigenetics and Stem Cells, Helmholtz Zentrum M\u00fcnchen\u2014German Research Center for Environmental Health , Munich 81377, Germany"},{"name":"Institute of Functional Epigenetics, Helmholtz Zentrum M\u00fcnchen\u2014German Research Center for Environmental Health , Munich 85764, Germany"},{"name":"Institute of Computational Biology, Helmholtz Zentrum M\u00fcnchen\u2014German Research Center for Environmental Health , Munich 85764, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4956-2843","authenticated-orcid":false,"given":"Antonio","family":"Scialdone","sequence":"additional","affiliation":[{"name":"Institute of Epigenetics and Stem Cells, Helmholtz Zentrum M\u00fcnchen\u2014German Research Center for Environmental Health , Munich 81377, Germany"},{"name":"Institute of Functional Epigenetics, Helmholtz Zentrum M\u00fcnchen\u2014German Research Center for Environmental Health , Munich 85764, Germany"},{"name":"Institute of Computational Biology, Helmholtz Zentrum M\u00fcnchen\u2014German Research Center 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