Machine Learning in Bioinformatics
An Approach to Protein Sequence Analysis
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Machine Learning in Bioinformatics: Analysis of protein sequence in Bioinformatics has emerged as a key area for the application of machine learning methods. Such tasks often require the development of new algorithms and their applications. Protein sequence data is typically of very high dimensions and complex. The designing of machine learning algorithms requires a systematic approach to design and understand the underlying problem. This book provides a comprehensive coverage to explain the application of machine learning techniques in bioinformatics. It provides introductory chapters on mach...
Machine Learning in Bioinformatics: Analysis of protein sequence in Bioinformatics has emerged as a key area for the application of machine learning methods. Such tasks often require the development of new algorithms and their applications. Protein sequence data is typically of very high dimensions and complex. The designing of machine learning algorithms requires a systematic approach to design and understand the underlying problem. This book provides a comprehensive coverage to explain the application of machine learning techniques in bioinformatics. It provides introductory chapters on machine learning and molecular biology for cross discipline audience. This book follows a practical approach by first defining a problem and hypothesis associated to protein translational modification. It provides an extensive review of the existing methods and describes the development and implementation of an algorithm called MAPRes. The application, evaluation and testing of the algorithm is also discussed in the detail. This book will be suitable for researchers and students engaged with machine learning and bioinformatics.
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