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Hon-Cheong So

Showing results (1-10 of 74) with videos related to

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Computational and Structural Biotechnology Journal|July 17, 2020
Turning genome-wide association study findings into opportunities for drug repositioningAlexandria Lau, Hon-Cheong So
IEEE Journal of Biomedical and Health Informatics|July 17, 2018
Drug Repositioning for Schizophrenia and Depression/Anxiety Disorders: A Machine Learning Approach Leveraging Expression DataKai Zhao, Hon-Cheong So
Methods in Molecular Biology (Clifton, N.J.)|December 15, 2018
Using Drug Expression Profiles and Machine Learning Approach for Drug RepurposingKai Zhao, Hon-Cheong So
Plos Genetics|December 15, 2010
A unifying framework for evaluating the predictive power of genetic variants based on the level of heritability explainedHon-Cheong So, Pak C Sham
Cold Spring Harbor Protocols|January 6, 2011
Multiple testing and power calculations in genetic association studiesHon-Cheong So, Pak C Sham
Journal of Psychiatric Research|January 1, 2019
Implications of de novo mutations in guiding drug discovery: A study of four neuropsychiatric disordersHon-Cheong So, Yui-Hang Wong
Scientific Reports|February 2, 2017
Improving polygenic risk prediction from summary statistics by an empirical Bayes approachHon-Cheong So, Pak C Sham
Bioinformatics (Oxford, England)|January 10, 2017
Exploring the predictive power of polygenic scores derived from genome-wide association studies: a study of 10 complex traitsHon-Cheong So, Pak C Sham
Behavior Genetics|February 10, 2011
Robust association tests under different genetic models, allowing for binary or quantitative traits and covariatesHon-Cheong So, Pak C Sham
Human Heredity|September 15, 2010
Effect size measures in genetic association studies and age-conditional risk predictionHon-Cheong So, Pak C Sham
Pageof 8

Showing results (1-10 of 74) with videos related to

Sort By:
Pageof 8
Computational and Structural Biotechnology Journal|July 17, 2020
Turning genome-wide association study findings into opportunities for drug repositioningAlexandria Lau, Hon-Cheong So
IEEE Journal of Biomedical and Health Informatics|July 17, 2018
Drug Repositioning for Schizophrenia and Depression/Anxiety Disorders: A Machine Learning Approach Leveraging Expression DataKai Zhao, Hon-Cheong So
Methods in Molecular Biology (Clifton, N.J.)|December 15, 2018
Using Drug Expression Profiles and Machine Learning Approach for Drug RepurposingKai Zhao, Hon-Cheong So
Plos Genetics|December 15, 2010
A unifying framework for evaluating the predictive power of genetic variants based on the level of heritability explainedHon-Cheong So, Pak C Sham
Cold Spring Harbor Protocols|January 6, 2011
Multiple testing and power calculations in genetic association studiesHon-Cheong So, Pak C Sham
Journal of Psychiatric Research|January 1, 2019
Implications of de novo mutations in guiding drug discovery: A study of four neuropsychiatric disordersHon-Cheong So, Yui-Hang Wong
Scientific Reports|February 2, 2017
Improving polygenic risk prediction from summary statistics by an empirical Bayes approachHon-Cheong So, Pak C Sham
Bioinformatics (Oxford, England)|January 10, 2017
Exploring the predictive power of polygenic scores derived from genome-wide association studies: a study of 10 complex traitsHon-Cheong So, Pak C Sham
Behavior Genetics|February 10, 2011
Robust association tests under different genetic models, allowing for binary or quantitative traits and covariatesHon-Cheong So, Pak C Sham
Human Heredity|September 15, 2010
Effect size measures in genetic association studies and age-conditional risk predictionHon-Cheong So, Pak C Sham
Pageof 8