Bioinformatics: The Machine Learning Approach
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Bioinformatics is the application of tools of computation and analysis for capturing and interpreting biological data. Machine learning is a branch of artificial intelligence and computer science that has applications in multiple fields. Machine learning in bioinformatics involves the application of machine learning algorithms to bioinformatics such as proteomics, genomics, microarrays, evolution, text mining and systems biology. Genomics is a prominent area of bioinformatics involved in the study of genome mapping, genomic expression regulation, and genome evolution and editing. In medical di...
Bioinformatics is the application of tools of computation and analysis for capturing and interpreting biological data. Machine learning is a branch of artificial intelligence and computer science that has applications in multiple fields. Machine learning in bioinformatics involves the application of machine learning algorithms to bioinformatics such as proteomics, genomics, microarrays, evolution, text mining and systems biology. Genomics is a prominent area of bioinformatics involved in the study of genome mapping, genomic expression regulation, and genome evolution and editing. In medical diagnostics, some of the major applications of machine learning in genomics are genome sequencing, gene editing, and improving clinical workflow. This book outlines a machine learning approach towards bioinformatics. A number of latest researches have been included to keep the readers updated with the global concepts in this area of study. It aims to serve as a resource guide for students and experts alike and contribute to the growth of the discipline.
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