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CAGI6 ID-Challenge: Assessment of phenotype and variant predictions in 415 children with Neurodevelopmental Disorders (NDDs).
Aspromonte, Maria Cristina; Conte, Alessio Del; Zhu, Shaowen; Tan, Wuwei; Shen, Yang; Zhang, Yexian; Li, Qi; Wang, Maggie Haitian; Babbi, Giulia; Bovo, Samuele; Martelli, Pier Luigi; Casadio, Rita; Althagafi, Azza; Toonsi, Sumyyah; Kulmanov, Maxat; Hoehndorf, Robert; Katsonis, Panagiotis; Williams, Amanda; Lichtarge, Olivier; Xian, Su; Surento, Wesley; Pejaver, Vikas; Mooney, Sean D; Sunderam, Uma; Srinivasan, Rajgopal; Murgia, Alessandra; Piovesan, Damiano; Tosatto, Silvio C E; Leonardi, Emanuela.
  • Aspromonte MC; Department of Biomedical Sciences, University of Padova.
  • Conte AD; Department of Biomedical Sciences, University of Padova.
  • Zhu S; Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843.
  • Tan W; Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843.
  • Shen Y; Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843.
  • Zhang Y; CUHK Shenzhen Research Institute, Shenzhen.
  • Li Q; CUHK Shenzhen Research Institute, Shenzhen.
  • Wang MH; CUHK Shenzhen Research Institute, Shenzhen.
  • Babbi G; Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna.
  • Bovo S; Department of Agricultural and Food Sciences, University of Bologna.
  • Martelli PL; Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna.
  • Casadio R; Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna.
  • Althagafi A; Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences & Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23.
  • Toonsi S; Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences & Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23.
  • Kulmanov M; Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences & Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23.
  • Hoehndorf R; Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences & Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23.
  • Katsonis P; Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030.
  • Williams A; Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030.
  • Lichtarge O; Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030.
  • Xian S; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195.
  • Surento W; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195.
  • Pejaver V; Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029.
  • Mooney SD; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195.
  • Sunderam U; Innovation Labs, Tata Consultancy Services, Hyderabad.
  • Srinivasan R; Innovation Labs, Tata Consultancy Services, Hyderabad.
  • Murgia A; Department of Women's and Children's Health, University of Padova.
  • Piovesan D; Department of Biomedical Sciences, University of Padova.
  • Tosatto SCE; Department of Biomedical Sciences, University of Padova.
  • Leonardi E; Department of Biomedical Sciences, University of Padova.
Res Sq ; 2023 Aug 02.
Article en En | MEDLINE | ID: mdl-37577579
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Año: 2023 Tipo del documento: Article
Texto completo
Imprimir
XML
PubMed Links
Search on Google

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Año: 2023 Tipo del documento: Article