Abstract
Human genome informatics is the application of information theory, including computer science and statistics, to the field of human genomics. We frame the challenge of understanding the human genome and controlling disease processes in terms of computation (the Turing machine), Kolmogorov complexity, Occam's razor, the law of requisite variety, Moore's Law, and how abstraction, computation, and collaboration expand our capacity to intervene in genomic processes, despite their enormous complexity. We follow this with an overview of the application of human genome informatics in genomics research and genomic medicine, focusing in particular on informatics solutions for analysis of data resulting from high-throughput microarray-based genotyping and next-generation sequencing, cytogenetics analysis, proteomics and metabolomics analysis, and variant annotation and reporting. Special emphasis is also given on genomic databases, artificial intelligence and machine learning, and translational tools and solutions for pharmacogenomics, while we also allude to the concept of genomic data sharing as an important new trend in genomics with huge social and technical implications and challenges of realizing the full potential of collaborative science in genomics research and genomic medicine.
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