Gene- and domain-aware calibration increases the clinical utility of variant effect predictors.
Saved in:
| Title: | Gene- and domain-aware calibration increases the clinical utility of variant effect predictors. |
|---|---|
| Authors: | Chen Y; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA.; Department of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; These authors contributed equally., Fayer S; Department of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; These authors contributed equally., Jain S; The Institute for Experiential AI, Northeastern University, Boston, MA, USA., Benazouz M; Department of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; Molecular Engineering and Sciences Institute, University of Washington, Seattle, WA, USA., Sverchkov Y; Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, USA., Stone J; Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA., Sharma H; Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA., Bergquist T; Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA., Stewart R; Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA., Mooney SD; Cyberinfrastructure and Artificial Intelligence Platforms Section, Center for Genomics and Data Science Research, National Human Genome Research Institute, Bethesda, MD, USA., Craven M; Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, USA., Radivojac P; Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA., Starita LM; Department of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA., Fowler DM; Department of Genome Sciences, School of Medicine, University of Washington, Seattle, WA, USA.; Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.; Department of Bioengineering, University of Washington, Seattle, WA, USA., Pejaver V; Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.; Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA. |
| Source: | Research square [Res Sq] 2026 May 08. Date of Electronic Publication: 2026 May 08. |
| Publication Type: | Journal Article; Preprint |
| Journal Info: | Country of Publication: United States NLM ID: 101768035 Publication Model: Electronic Cited Medium: Internet ISSN: 2693-5015 (Electronic) Linking ISSN: 26935015 NLM ISO Abbreviation: Res Sq Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
Be the first to leave a comment!
