Introduction to Machine Learning and Bioinformatics by Mitra, Datta, Perkins

Introduction to Machine Learning and Bioinformatics by Mitra, Datta, Perkins

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Machine learning and bioinformatics are two rapidly advancing fields that are revolutionizing the way we approach biological research and data analysis. In their book “Introduction to Machine Learning and Bioinformatics,” authors Mitra, Datta, and Perkins provide a comprehensive overview of the key concepts and techniques in these areas.

Machine learning refers to the development of algorithms and statistical models that enable computers to learn from and make predictions or decisions based on data. In the context of bioinformatics, machine learning is used to analyze and interpret biological data, such as DNA sequences, protein structures, and gene expression patterns.

The book covers a wide range of topics, including:

– Basics of machine learning algorithms and their applications in bioinformatics
– Data preprocessing and feature selection techniques
– Classification, clustering, and regression methods
– Deep learning and neural networks
– Applications of machine learning in genomics, proteomics, and drug discovery

By combining their expertise in machine learning and bioinformatics, Mitra, Datta, and Perkins offer a unique perspective on how these two fields can be integrated to address complex biological problems. Whether you are a student, researcher, or industry professional, this book provides a valuable introduction to the exciting intersection of machine learning and bioinformatics.
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