{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T23:28:24Z","timestamp":1776900504676,"version":"3.51.2"},"reference-count":54,"publisher":"Oxford University Press (OUP)","issue":"6","license":[{"start":{"date-parts":[[2021,12,22]],"date-time":"2021-12-22T00:00:00Z","timestamp":1640131200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001821","name":"Vienna Science and Technology Fund","doi-asserted-by":"publisher","award":["VRG15-005"],"award-info":[{"award-number":["VRG15-005"]}],"id":[{"id":"10.13039\/501100001821","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001821","name":"Vienna Science and Technology Fund","doi-asserted-by":"publisher","award":["LS16-060"],"award-info":[{"award-number":["LS16-060"]}],"id":[{"id":"10.13039\/501100001821","id-type":"DOI","asserted-by":"publisher"}]},{"name":"CNRS (International Research Project SysTact"},{"name":"DOC-fellowship of the Austrian Academy of Sciences","award":["25525"],"award-info":[{"award-number":["25525"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,3,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>High-content imaging screens provide a cost-effective and scalable way to assess cell states across diverse experimental conditions. The analysis of the acquired microscopy images involves assembling and curating raw cellular measurements into morphological profiles suitable for testing biological hypotheses. Despite being a critical step, general-purpose and adaptable tools for morphological profiling are lacking and no solution is available for the high-performance Julia programming language.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Here, we introduce BioProfiling.jl, an efficient end-to-end solution for compiling and filtering informative morphological profiles in Julia. The package contains all the necessary data structures to curate morphological measurements and helper functions to transform, normalize and visualize profiles. Robust statistical distances and permutation tests enable quantification of the significance of the observed changes despite the high fraction of outliers inherent to high-content screens. This package also simplifies visual artifact diagnostics, thus streamlining a bottleneck of morphological analyses. We showcase the features of the package by analyzing a chemical imaging screen, in which the morphological profiles prove to be informative about the compounds' mechanisms of action and can be conveniently integrated with the network localization of molecular targets.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The Julia package is available on GitHub: https:\/\/github.com\/menchelab\/BioProfiling.jl. We also provide Jupyter notebooks reproducing our analyses: https:\/\/github.com\/menchelab\/BioProfilingNotebooks. The data underlying this article are available from FigShare, at https:\/\/doi.org\/10.6084\/m9.figshare.14784678.v2.<\/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\/btab853","type":"journal-article","created":{"date-parts":[[2021,12,16]],"date-time":"2021-12-16T15:13:08Z","timestamp":1639667588000},"page":"1692-1699","source":"Crossref","is-referenced-by-count":8,"title":["BioProfiling.jl: profiling biological perturbations with high-content imaging in single cells and heterogeneous populations"],"prefix":"10.1093","volume":"38","author":[{"given":"Loan","family":"Vulliard","sequence":"first","affiliation":[{"name":"CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences , Vienna 1090, 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Cancer Center , Vienna 1090, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vanja","family":"Nagy","sequence":"additional","affiliation":[{"name":"CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences , Vienna 1090, Austria"},{"name":"Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases , Vienna 1090, Austria"},{"name":"Department of Neurology, Medical University of Vienna , Vienna 1090, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lo\u00efc","family":"Dupr\u00e9","sequence":"additional","affiliation":[{"name":"Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases , Vienna 1090, Austria"},{"name":"Department of Dermatology, Medical University of Vienna , Vienna 1090, Austria"},{"name":"Toulouse Institute for Infectious and Inflammatory Diseases (INFINITy), INSERM UMR1291, CNRS UMR5051, Toulouse III Paul Sabatier University , Toulouse 31024, 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