Data analytics in bioinformatics : a machine learning perspective /
"Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vit...
| Other Authors: | , , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Hoboken, NJ :
John Wiley & Sons, Inc.,
2021.
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | "Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more"-- |
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| Physical Description: | 1 online resource (xxi, 513 pages) : illustrations (some color) |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9781119785620 1119785626 9781119785606 111978560X 9781119785613 1119785618 |