المؤلفون: Umarov, Ramzan, Kuwahara, Hiroyuki, Li, Yu, Gao, Xin, Solovyev, Victor

مصطلحات موضوعية: Quantitative Biology - Genomics, Computer Science - Machine Learning, Statistics - Machine Learning

الوصول الحر: http://arxiv.org/abs/1810.01414Test

المؤلفون: Shim, Injeong, Kuwahara, Hiroyuki, Chen, NingNing, Hashem, Mais O., AlAbdi, Lama, Abouelhoda, Mohamed, Won, Hong-Hee, Natarajan, Pradeep, Ellinor, Patrick T., Khera, Amit V., Gao, Xin, Alkuraya, Fowzan S., Fahed, Akl C.

المساهمون: Computational Biosciences Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia, Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia, Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division, Bioscience Program, Biological and Environmental Science and Engineering (BESE) Division, Computer Science Program, Cardiovascular Research Center, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA, Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Samsung Medical Center, Seoul, South Korea, Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA, Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA, Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia, Department of Zoology, College of Science, King Saud University, Riyadh, Saudi Arabia, Department of Computation Sciences, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia, Verve Therapeutics, Cambridge, MA, USA

وصف الملف: application/pdf

العلاقة: https://www.nature.com/articles/s41467-023-41985-1Test; Shim, I., Kuwahara, H., Chen, N., Hashem, M. O., AlAbdi, L., Abouelhoda, M., Won, H.-H., Natarajan, P., Ellinor, P. T., Khera, A. V., Gao, X., Alkuraya, F. S., & Fahed, A. C. (2023). Clinical utility of polygenic scores for cardiometabolic disease in Arabs. Nature Communications, 14(1). https://doi.org/10.1038/s41467-023-41985-1Test; 2-s2.0-85174455165; Nature Communications; http://hdl.handle.net/10754/695719Test; 14

الإتاحة: https://doi.org/10.1038/s41467-023-41985-1Test
http://hdl.handle.net/10754/695719Test

المؤلفون: Bhattacharya, Romit, Chen, NingNing, Shim, Injeong, Kuwahara, Hiroyuki, Gao, Xin, Alkuraya, Fowzan S., Fahed, Akl C.

المساهمون: Computational Biosciences Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia, Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia, Bioscience Program, Biological and Environmental Science and Engineering (BESE) Division, Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division, Computer Science Program, Department of Medicine, Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, 185 Cambridge Street, Department of Medicine, Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA, Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA, Department of Digital Health, Samsung Medical Center, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, Republic of South Korea, Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Kingdom of Saudi Arabia

وصف الملف: application/pdf

العلاقة: https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-023-01254-8Test; Genome Medicine; http://hdl.handle.net/10754/695812Test; 15

الإتاحة: https://doi.org/10.1186/s13073-023-01254-8Test
http://hdl.handle.net/10754/695812Test

المؤلفون: Malawsky, Daniel S, van Walree, Eva, Jacobs, Benjamin M, Heng, Teng Hiang, Huang, Qin Qin, Sabir, Ataf H, Rahman, Saadia, Sharif, Saghira Malik, Khan, Ahsan, Mirkov, Maša Umićević, 23andMe Research Team, Genes & Health Research Team, Kuwahara, Hiroyuki, Gao, Xin, Alkuraya, Fowzan S, Posthuma, Danielle, Newman, William G, Griffiths, Christopher J, Mathur, Rohini, van Heel, David A, Finer, Sarah, O'Connell, Jared, Martin, Hilary C

المساهمون: Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division, Computer Science Program, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK., Department of Clinical Genetics, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands, Department of Complex Trait Genetics Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU Amsterdam, Amsterdam, the Netherlands., Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK, Wolfson Institute of Population Health, Queen Mary University of London, London, UK., West Midlands Regional Clinical Genetics Unit, Birmingham Women's and Children's NHS FT, Birmingham, UK, Institute of Cancer and Genomics, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK., Queen Square Institute of Neurology, University College London, London, UK., Yorkshire Regional Genetics Service, Leeds Teaching Hospitals NHS Trust, Leeds, UK., Waltham Forest Council, Waltham Forest Town Hall, Forest Road, Walthamstow E17 4JF, UK., Congenica Limited, BioData Innovation Centre, Wellcome Genome Campus, Hinxton, UK., Department of Translational Genomics, Center for Genomic Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia., Division of Evolution, Infection and Genomics, Faculty of Biology, Medicine and Human Sciences, University of Manchester, Manchester M13 9PL, UK, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester M13 9WL, UK., Wolfson Institute of Population Health, Queen Mary University of London, London, UK, MRC and Asthma UK Centre in Allergic Mechanisms of Asthma, King's College London, London, UK., Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK., 23andMe, Inc., Sunnyvale, CA, USA.

مصطلحات موضوعية: Consanguinity, Medical genetics, Recessive, Autozygosity, Common Diseases, Diverse Cohorts

وصف الملف: application/pdf; application/zip

العلاقة: https://linkinghub.elsevier.com/retrieve/pii/S0092867423009182Test; Malawsky, D. S., van Walree, E., Jacobs, B. M., Heng, T. H., Huang, Q. Q., Sabir, A. H., Rahman, S., Sharif, S. M., Khan, A., Mirkov, M. U., Kuwahara, H., Gao, X., Alkuraya, F. S., Posthuma, D., Newman, W. G., Griffiths, C. J., Mathur, R., van Heel, D. A., Finer, S., … Martin, H. C. (2023). Influence of autozygosity on common disease risk across the phenotypic spectrum. Cell. https://doi.org/10.1016/j.cell.2023.08.028Test; Cell; http://hdl.handle.net/10754/694820Test

الإتاحة: https://doi.org/10.1016/j.cell.2023.08.028Test
http://hdl.handle.net/10754/694820Test

المؤلفون: Kuwahara, Hiroyuki, Gao, Xin

المساهمون: King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE) , Thuwal, 23955-6900, Saudi Arabia, Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division, Computer Science Program

وصف الملف: application/pdf

العلاقة: github:hkuwahara/sleaping; Kuwahara, H., & Gao, X. (2023). S-leaping: an efficient downsampling method for large high-throughput sequencing data. Bioinformatics. https://doi.org/10.1093/bioinformatics/btad399Test; Bioinformatics; PMC10318387; http://hdl.handle.net/10754/692923Test

الإتاحة: https://doi.org/10.1093/bioinformatics/btad399Test
http://hdl.handle.net/10754/692923Test

المؤلفون: Sakai, Yoichi, Muranaka, Yu, Nakayama, Hiromi, Baba, Koji, Matsushita, Kazuya, Kuwahara, Hiroyuki, Kuniyoshi, Hisato

المصدر: Journal of Fish Biology; Apr2024, Vol. 104 Issue 4, p979-988, 10p

مصطلحات موضوعية: EGGS, GENDER transition, PITUITARY gland, EGG incubation, FEMALES, HUMAN sexuality, MALES

المؤلفون: Li, Yu, Chen, Siyuan, Rapakoulia, Trisevgeni, Kuwahara, Hiroyuki, Yip, Kevin Y, Gao, Xin

المساهمون: Computational Bioscience Research Center (CBRC), Computer Science, Computer Science Program, Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division, Structural and Functional Bioinformatics Group, Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China, The CUHK Shenzhen Research Institute, Hi-Tech Park, Nanshan, Shenzhen 518057, China, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, 14195 Berlin, Germany

وصف الملف: application/pdf

العلاقة: github:frankchen121212/RHSNet; Li, Y., Chen, S., Rapakoulia, T., Kuwahara, H., Yip, K. Y., & Gao, X. (2022). Deep learning identifies and quantifies recombination hotspot determinants. Bioinformatics. https://doi.org/10.1093/bioinformatics/btac234Test; Bioinformatics; http://hdl.handle.net/10754/676242Test

الإتاحة: https://doi.org/10.1093/bioinformatics/btac234Test
http://hdl.handle.net/10754/676242Test

المؤلفون: Kuwahara, Hiroyuki, Gao, Xin

المساهمون: Computational Bioscience Research Center (CBRC), Computer Science Program, Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division, Structural and Functional Bioinformatics Group

وصف الملف: application/pdf

العلاقة: https://jcheminf.biomedcentral.com/articles/10.1186/s13321-021-00506-2Test; Kuwahara, H., & Gao, X. (2021). Analysis of the effects of related fingerprints on molecular similarity using an eigenvalue entropy approach. Journal of Cheminformatics, 13(1). doi:10.1186/s13321-021-00506-2; Journal of Cheminformatics; http://hdl.handle.net/10754/668228Test; 13

الإتاحة: https://doi.org/10.1186/s13321-021-00506-2Test
https://doi.org/10.1101/853762Test
http://hdl.handle.net/10754/668228Test

المؤلفون: Shamseldin, Hanan E, AlAbdi, Lama, Maddirevula, Sateesh, Alsaif, Hessa S, AlZahrani, Fatema, Ewida, Nour, Hashem, Mais, Abdulwahab, Firdous, Abuyousef, Omar, Kuwahara, Hiroyuki, Gao, Xin, Molecular Autopsy Consortium, Alkuraya, Fowzan S

المساهمون: Computational Bioscience Research Center (CBRC), Computer Science Program, Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division, Structural and Functional Bioinformatics Group

مصطلحات موضوعية: Loss Of Function, Multi-locus, Bmpr1a, Msn, Founder, Embryonic Lethal, Faah2, Ehbp1l1

وصف الملف: application/pdf

العلاقة: https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-021-00973-0Test; Shamseldin, H. E., AlAbdi, L., Maddirevula, S., Alsaif, H. S., Alzahrani, F., … Ewida, N. (2021). Lethal variants in humans: lessons learned from a large molecular autopsy cohort. Genome Medicine, 13(1). doi:10.1186/s13073-021-00973-0; Genome medicine; http://hdl.handle.net/10754/672884Test; 13

الإتاحة: https://doi.org/10.1186/s13073-021-00973-0Test
http://hdl.handle.net/10754/672884Test

المؤلفون: Kuwahara, Hiroyuki, Gao, Xin

المساهمون: King Abdullah University of Science and Technology

المصدر: Nature Computational Science ; volume 1, issue 1, page 62-70 ; ISSN 2662-8457

مصطلحات موضوعية: Computer Networks and Communications, Computer Science Applications, Computer Science (miscellaneous)

الإتاحة: https://doi.org/10.1038/s43588-020-00001-yTest
https://www.nature.com/articles/s43588-020-00001-y.pdfTest
https://www.nature.com/articles/s43588-020-00001-yTest