{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T11:44:15Z","timestamp":1753875855501,"version":"3.41.2"},"reference-count":18,"publisher":"Oxford University Press (OUP)","issue":"9","license":[{"start":{"date-parts":[[2024,8,27]],"date-time":"2024-08-27T00:00:00Z","timestamp":1724716800000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000025","name":"NIMH","doi-asserted-by":"publisher","award":["1R44MH135465"],"award-info":[{"award-number":["1R44MH135465"]}],"id":[{"id":"10.13039\/100000025","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,9,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Summary<\/jats:title>\n                  <jats:p>We introduce Eliater, a Python package for estimating the effect of perturbation of an upstream molecule on a downstream molecule in a biomolecular network. The estimation takes as input a biomolecular network, observational biomolecular data, and a perturbation of interest, and outputs an estimated quantitative effect of the perturbation. We showcase the functionalities of Eliater in a case study of Escherichia coli transcriptional regulatory network.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The code, the documentation, and several case studies are available open source at https:\/\/github.com\/y0-causal-inference\/eliater.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btae527","type":"journal-article","created":{"date-parts":[[2024,8,24]],"date-time":"2024-08-24T15:40:38Z","timestamp":1724514038000},"source":"Crossref","is-referenced-by-count":0,"title":["<tt>Eliater<\/tt>: a Python package for estimating outcomes of perturbations in biomolecular 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