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Full-Text Articles in Life Sciences
Machine Learning And Genome Annotation: A Match Meant To Be?, Kevin Y. Yip, Chao Cheng, Mark Gerstein
Machine Learning And Genome Annotation: A Match Meant To Be?, Kevin Y. Yip, Chao Cheng, Mark Gerstein
Dartmouth Scholarship
By its very nature, genomics produces large, high-dimensional datasets that are well suited to analysis by machine learning approaches. Here, we explain some key aspects of machine learning that make it useful for genome annotation, with illustrative examples from ENCODE.
Chapter 11: Genome-Wide Association Studies, William S. Bush, Jason H. Moore
Chapter 11: Genome-Wide Association Studies, William S. Bush, Jason H. Moore
Dartmouth Scholarship
Genome-wide association studies (GWAS) have evolved over the last ten years into a powerful tool for investigating the genetic architecture of human disease. In this work, we review the key concepts underlying GWAS, including the architecture of common diseases, the structure of common human genetic variation, technologies for capturing genetic information, study designs, and the statistical methods used for data analysis. We also look forward to the future beyond GWAS.