{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:34:01Z","timestamp":1772138041933,"version":"3.50.1"},"reference-count":71,"publisher":"Oxford University Press (OUP)","issue":"9","license":[{"start":{"date-parts":[[2020,11,2]],"date-time":"2020-11-02T00:00:00Z","timestamp":1604275200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["AI087794"],"award-info":[{"award-number":["AI087794"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["GM129126"],"award-info":[{"award-number":["GM129126"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,6,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>The activity of a transcription factor (TF) in a sample of cells is the extent to which it is exerting its regulatory potential. Many methods of inferring TF activity from gene expression data have been described, but due to the lack of appropriate large-scale datasets, systematic and objective validation has not been possible until now.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We systematically evaluate and optimize the approach to TF activity inference in which a gene expression matrix is factored into a condition-independent matrix of control strengths and a condition-dependent matrix of TF activity levels. We find that expression data in which the activities of individual TFs have been perturbed are both necessary and sufficient for obtaining good performance. To a considerable extent, control strengths inferred using expression data from one growth condition carry over to other conditions, so the control strength matrices derived here can be used by others. Finally, we apply these methods to gain insight into the upstream factors that regulate the activities of yeast TFs Gcr2, Gln3, Gcn4 and Msn2.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>Evaluation code and data are available at https:\/\/doi.org\/10.5281\/zenodo.4050573.<\/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\/btaa947","type":"journal-article","created":{"date-parts":[[2020,10,27]],"date-time":"2020-10-27T16:13:52Z","timestamp":1603815232000},"page":"1234-1245","source":"Crossref","is-referenced-by-count":31,"title":["Inferring TF activities and activity regulators from gene expression data with constraints from TF perturbation data"],"prefix":"10.1093","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6706-2466","authenticated-orcid":false,"given":"Cynthia Z","family":"Ma","sequence":"first","affiliation":[{"name":"Center for Genome Sciences and Systems Biology, Washington University School of Medicine , St. Louis, MO 63110, USA"},{"name":"Department of Computer Science and Engineering, Washington University , St. Louis, MO 63130, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8689-0299","authenticated-orcid":false,"given":"Michael R","family":"Brent","sequence":"additional","affiliation":[{"name":"Center for Genome Sciences and Systems Biology, Washington University School of Medicine , St. Louis, MO 63110, USA"},{"name":"Department of Computer Science and Engineering, Washington University , St. Louis, MO 63130, USA"},{"name":"Department of Genetics, Washington University School of Medicine , St. Louis, MO 63110, USA"}]}],"member":"286","published-online":{"date-parts":[[2020,12,22]]},"reference":[{"key":"2023051706063801300_btaa947-B1","doi-asserted-by":"crossref","first-page":"838","DOI":"10.1038\/ng.3593","article-title":"Functional characterization of somatic mutations in cancer using network-based inference of protein activity","volume":"48","author":"Alvarez","year":"2016","journal-title":"Nat. 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