{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:34:06Z","timestamp":1772138046326,"version":"3.50.1"},"reference-count":17,"publisher":"Oxford University Press (OUP)","issue":"21","license":[{"start":{"date-parts":[[2021,7,2]],"date-time":"2021-07-02T00:00:00Z","timestamp":1625184000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Fondation Toulouse Cancer Sant\u00e9 and Pierre Fabre Research Institute"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,11,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>Networks provide a powerful framework to analyze spatial omics experiments. However, we lack tools that integrate several methods to easily reconstruct networks for further analyses with dedicated libraries. In addition, choosing the appropriate method and parameters can be challenging. We propose tysserand, a Python library to reconstruct spatial networks from spatially resolved omics experiments. It is intended as a common tool to which the bioinformatics community can add new methods to reconstruct networks, choose appropriate parameters, clean resulting networks and pipe data to other libraries.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>tysserand software and tutorials with a Jupyter notebook to reproduce the results are available at https:\/\/github.com\/VeraPancaldiLab\/tysserand.<\/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\/btab490","type":"journal-article","created":{"date-parts":[[2021,6,30]],"date-time":"2021-06-30T15:22:52Z","timestamp":1625066572000},"page":"3989-3991","source":"Crossref","is-referenced-by-count":7,"title":["Tysserand\u2014fast and accurate reconstruction of spatial networks from bioimages"],"prefix":"10.1093","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3164-6640","authenticated-orcid":false,"given":"Alexis","family":"Coullomb","sequence":"first","affiliation":[{"name":"Department of Bioinformatics, Centre de Recherches en Canc\u00e9rologie de Toulouse, INSERM , Occitanie 31100, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7433-624X","authenticated-orcid":false,"given":"Vera","family":"Pancaldi","sequence":"additional","affiliation":[{"name":"Department of Bioinformatics, Centre de Recherches en Canc\u00e9rologie de Toulouse, INSERM , Occitanie 31100, France"}]}],"member":"286","published-online":{"date-parts":[[2021,7,2]]},"reference":[{"key":"2023051608251553800_btab490-B1","first-page":"122","article-title":"The opencv library Dr. Dobb\u2019s","volume":"120","author":"Bradski","year":"2000","journal-title":"J. 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