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Their ability to evaluate a wide spectrum of interventions, from single drugs to intricate drug combinations and CRISPR-interference, has established them as an invaluable resource for the development of novel therapeutic approaches. Nevertheless, the combinatorial complexity of potential interventions makes a comprehensive exploration intractable. Hence, prioritizing interventions for further experimental investigation becomes of utmost importance.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We propose CODEX (COunterfactual Deep learning for the in silico EXploration of cancer cell line perturbations) as a general framework for the causal modeling of HTS data, linking perturbations to their downstream consequences. CODEX relies on a stringent causal modeling strategy based on counterfactual reasoning. As such, CODEX predicts drug-specific cellular responses, comprising cell survival and molecular alterations, and facilitates the in silico exploration of drug combinations. This is achieved for both bulk and single-cell HTS. We further show that CODEX provides a rationale to explore complex genetic modifications from CRISPR-interference in silico in single cells.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>Our implementation of CODEX is publicly available at https:\/\/github.com\/sschrod\/CODEX. All data used in this article are publicly available.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btae261","type":"journal-article","created":{"date-parts":[[2024,6,28]],"date-time":"2024-06-28T09:37:07Z","timestamp":1719567427000},"page":"i91-i99","source":"Crossref","is-referenced-by-count":7,"title":["CODEX: COunterfactual Deep learning for the <i>in silico<\/i> EXploration of cancer cell line perturbations"],"prefix":"10.1093","volume":"40","author":[{"given":"Stefan","family":"Schrod","sequence":"first","affiliation":[{"name":"Department of Medical Bioinformatics, University Medical Center G\u00f6ttingen , 37077 Niedersachsen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Helena U","family":"Zacharias","sequence":"additional","affiliation":[{"name":"Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Hannover Medical School , 30625 Hannover, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tim","family":"Bei\u00dfbarth","sequence":"additional","affiliation":[{"name":"Department of Medical Bioinformatics, University Medical Center G\u00f6ttingen , 37077 Niedersachsen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anne-Christin","family":"Hauschild","sequence":"additional","affiliation":[{"name":"Department of Medical Informatics, University Medical Center G\u00f6ttingen , 37075 Niedersachsen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Altenbuchinger","sequence":"additional","affiliation":[{"name":"Department of Medical Bioinformatics, University Medical Center G\u00f6ttingen , 37077 Niedersachsen, 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