ArticleHuman mutation2017
Working toward precision medicine: Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges.
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Article in Human mutation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses that pooled it.
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34citing papers in PubMed, 2 pooled it
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Who cites it
34 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A Systematic Review of Artificial Intelligence and Machine Learning Applications to Inflammatory Bowel Disease, with Practical Guidelines for Interpretation.Inflammatory bowel diseases · 2022Pooled it
- Machine learning for genetic prediction of psychiatric disorders: a systematic review.Molecular psychiatry · 2021Pooled it
- Genomic prediction with kinship-based multiple kernel learning produces hypothesis on the underlying inheritance mechanisms of phenotypic traits.Genome biology · 2025Article
- Digital biomarkers and artificial intelligence: a new frontier in personalized management of inflammatory bowel disease.Frontiers in immunology · 2025Review
- Artificial intelligence in autoimmune diseases: a bibliometric exploration of the past two decades.Frontiers in immunology · 2025Review
- Biologically meaningful genome interpretation models to address data underdetermination for the leaf and seed ionome prediction in Arabidopsis thaliana.Scientific reports · 2024Article
- Advances in Inflammatory Bowel Disease Diagnostics: Machine Learning and Genomic Profiling Reveal Key Biomarkers for Early Detection.Diagnostics (Basel, Switzerland) · 2024Article
- CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods.Genome biology · 2024Article
- Evaluation of crowdsourced mortality prediction models as a framework for assessing artificial intelligence in medicine.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Genome interpretation in a federated learning context allows the multi-center exome-based risk prediction of Crohn's disease patients.Scientific reports · 2023Article
- Implementation of ensemble machine learning algorithms on exome datasets for predicting early diagnosis of cancers.BMC bioinformatics · 2022Article
- Genome interpretation using in silico predictors of variant impact.Human genetics · 2022Review
- From genotype to phenotype in Arabidopsis thaliana: in-silico genome interpretation predicts 288 phenotypes from sequencing data.Nucleic acids research · 2022Article
- Discriminating head trauma outcomes using machine learning and genomics.Journal of molecular medicine (Berlin, Germany) · 2022Article
- Editorial: Towards genome interpretation: Computational methods to model the genotype-phenotype relationship.Frontiers in bioinformatics · 2022Article
- Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks.Nature communications · 2021Article
- DOME: recommendations for supervised machine learning validation in biology.Nature methods · 2021Article
- Reviewing Challenges of Predicting Protein Melting Temperature Change Upon Mutation Through the Full Analysis of a Highly Detailed Dataset with High-Resolution Structures.Molecular biotechnology · 2021Review
- Review
- New approaches to predict the effect of co-occurring variants on protein characteristics.American journal of human genetics · 2021Article
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Authors and funding
51 authors.
Roxana DaneshjouDepartment of Genetics, Stanford School of Medicine, Stanford, California.ORCID 0000-0001-7988-9356
Yanran WangDepartment of Biochemistry and Microbiology, Rutgers University, New Brunswick, New Jersey.
Yana BrombergDepartment of Biochemistry and Microbiology, Rutgers University, New Brunswick, New Jersey.
Samuele BovoBiocomputing Group, BiGeA/CIG, "Luigi Galvani" Interdepartmental Center for Integrated Studies of Bioinformatics, Biophysics, and Biocomplexity, University of Bologna, Bologna, Italy.
Pier L MartelliBiocomputing Group, BiGeA/CIG, "Luigi Galvani" Interdepartmental Center for Integrated Studies of Bioinformatics, Biophysics, and Biocomplexity, University of Bologna, Bologna, Italy.
Giulia BabbiBiocomputing Group, BiGeA/CIG, "Luigi Galvani" Interdepartmental Center for Integrated Studies of Bioinformatics, Biophysics, and Biocomplexity, University of Bologna, Bologna, Italy.
Pietro Di LenaBiocomputing Group/Department of Computer Science and Engineering, University of Bologna, Bologna, Italy.
Rita CasadioBiocomputing Group, BiGeA/CIG, "Luigi Galvani" Interdepartmental Center for Integrated Studies of Bioinformatics, Biophysics, and Biocomplexity, University of Bologna, Bologna, Italy.
Matthew EdwardsComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts.ORCID 0000-0002-5845-748X
David GiffordComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts.
David T JonesBioinformatics Group, Department of Computer Science, University College London, London, United Kingdom.
Laksshman SundaramLarge-scale Intelligent Systems Laboratory, NSF Center for Big Learning, University of Florida, Gainesville, Florida.
Rajendra Rana BhatLarge-scale Intelligent Systems Laboratory, NSF Center for Big Learning, University of Florida, Gainesville, Florida.
Xiaolin LiLarge-scale Intelligent Systems Laboratory, NSF Center for Big Learning, University of Florida, Gainesville, Florida.
Lipika R PalInstitute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland.
Kunal KunduInstitute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland.
Yizhou YinInstitute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland.
John MoultInstitute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland.ORCID 0000-0002-3012-2282
Yuxiang JiangDepartment of Computer Science and Informatics, Indiana University, Bloomington, Indiana.
Vikas PejaverDepartment of Computer Science and Informatics, Indiana University, Bloomington, Indiana.
Kymberleigh A PagelDepartment of Computer Science and Informatics, Indiana University, Bloomington, Indiana.
Biao LiGilead Sciences, Foster City, California.
Sean D MooneyDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington.ORCID 0000-0003-2654-0833
Predrag RadivojacDepartment of Computer Science and Informatics, Indiana University, Bloomington, Indiana.
Sohela ShahQiagen Bioinformatics, Redwood City, California.
Marco CarraroDepartment of Biomedical Science, University of Padova, Padova, Italy.
Alessandra GaspariniDepartment of Biomedical Science, University of Padova, Padova, Italy.
Emanuela LeonardiDepartment of Woman and Child Health, University of Padova, Padova, Italy.
Manuel GiolloDepartment of Biomedical Science, University of Padova, Padova, Italy.
Carlo FerrariDepartment of Information Engineering, University of Padova, Padova, Italy.
Silvio C E TosattoDepartment of Biomedical Science, University of Padova, Padova, Italy.ORCID 0000-0003-4525-7793
Eran BacharThe Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel.
Johnathan R AzariaThe Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel.
Yanay OfranThe Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel.
Ron UngerThe Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel.
Abhishek NiroulaProtein Structure and Bioinformatics Group, Department of Experimental Medical Science, Lund University, Lund, Sweden.ORCID 0000-0002-5904-0635
Mauno VihinenProtein Structure and Bioinformatics Group, Department of Experimental Medical Science, Lund University, Lund, Sweden.
Billy ChangDivision of Biostatistics and Centre for Clinical Research and Biostatistics, JC School of Public Health and Primary Care, Chinese University of Hong Kong, Shatin, N.T., Hong Kong.
Maggie H WangDivision of Biostatistics and Centre for Clinical Research and Biostatistics, JC School of Public Health and Primary Care, Chinese University of Hong Kong, Shatin, N.T., Hong Kong.ORCID 0000-0003-1223-4595
Andre FrankeInstitute of Clinical Molecular Biology, Christian-Albrechts-University Kiel, Kiel, Germany.
Britt-Sabina PetersenInstitute of Clinical Molecular Biology, Christian-Albrechts-University Kiel, Kiel, Germany.
Mehdi PiroozniaDepartment of Psychiatry, The Johns Hopkins University School of Medicine, Baltimore, Maryland.
Peter ZandiDepartment of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Richard McCombieCold Spring Harbor Laboratory, Cold Spring Harbor, New York.
James B PotashDepartment of Psychiatry, University of Iowa, Iowa City, Iowa.
Russ B AltmanDepartment of Genetics, Stanford School of Medicine, Stanford, California.
Teri E KleinDepartment of Genetics, Stanford School of Medicine, Stanford, California.
Roger A HoskinsDepartment of Plant and Microbial Biology, University of California Berkeley, Berkeley, California.
Susanna RepoDepartment of Plant and Microbial Biology, University of California Berkeley, Berkeley, California.
Steven E BrennerDepartment of Plant and Microbial Biology, University of California Berkeley, Berkeley, California.
Alexander A MorganStanford School of Medicine, Stanford, California.
Funding
NIMH Center Repository Supporting Stem Cell ResearchU24MH068457 · NIMH · RUTGERS THE ST UNIV OF NJ NEW BRUNSWICK · PI BRZUSTOWICZ, LINDA M, KNOWLES, JAMES A · 2003 to 2024
$213.8MPharmGKB: pharmacogenomics knowledge for precision medicineR24GM061374 · NIGMS · STANFORD UNIVERSITY · PI ALTMAN, RUSS BIAGIO, KLEIN, TERI ELLEN · 2010 to 2018
$25.2MIntegrating data, algorithms and clinical reasoning for surgical risk assessmentR01GM110240 · NIGMS · UNIVERSITY OF FLORIDA · PI BIHORAC, AZRA, RASHIDI, PARISA · 2016 to 2025
$5.1MHigh-Throughput Native Context Mapping and Modeling of Regulatory DNAR01HG008754 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI GIFFORD, DAVID K · 2016 to 2019
$2.7MComponent 2 - Resource ProjectU41HG007346 · NHGRI · UNIVERSITY OF CALIFORNIA BERKELEY · PI BRENNER, STEVEN E · 2015 to 2017
$1.7MA computational framework for predicting the impact of mutations in autismR01MH105524 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI IAKOUCHEVA, LILIA M, RADIVOJAC, PREDRAG · 2014 to 2016
$1.4MAVA,Dx: Analysis of Variation for Association with DiseaseU01GM115486 · NIGMS · RUTGERS, THE STATE UNIV OF N.J. · PI BROMBERG, YANA · 2015 to 2018
$1.2MCritical Assessment of Genome Interpretation ConferenceR13HG006650 · NHGRI · UNIVERSITY OF CALIFORNIA BERKELEY · PI BRENNER, STEVEN E · 2011 to 2018
$165kNHGRI NIH HHS R01 HG008754NHGRI NIH HHS R13 HG006650NHGRI NIH HHS U41 HG007346NIGMS NIH HHS R01 GM110240NIGMS NIH HHS R24 GM061374NIGMS NIH HHS U01 GM115486NIMH NIH HHS R01 MH105524NIMH NIH HHS U24 MH068457
Abstract
Precision medicine aims to predict a patient's disease risk and best therapeutic options by using that individual's genetic sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype-phenotype prediction challenges; participants build models, undergo assessment, and share key findings. For CAGI 4, three challenges involved using exome-sequencing data: Crohn's disease, bipolar disorder, and warfarin dosing. Previous CAGI challenges included prior versions of the Crohn's disease challenge. Here, we discuss the range of techniques used for phenotype prediction as well as the methods used for assessing predictive models. Additionally, we outline some of the difficulties associated with making predictions and evaluating them. The lessons learned from the exome challenges can be applied to both research and clinical efforts to improve phenotype prediction from genotype. In addition, these challenges serve as a vehicle for sharing clinical and research exome data in a secure manner with scientists who have a broad range of expertise, contributing to a collaborative effort to advance our understanding of genotype-phenotype relationships.
Indexed as
Bipolar DisorderComputational BiologyCrohn DiseaseDatabases, GeneticExome SequencingGenetic Predisposition to DiseaseHumansInformation DisseminationPharmacogenomic VariantsPhenotypePrecision MedicineWarfarinWarfarinbipolar disorderCrohn's diseaseexomesmachine learningphenotype predictionwarfarin
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