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...
| Main Authors: | , , , , |
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| Format: | text |
| Language: | eng |
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Hoboken, NJ : Wiley-Scrivener,
2021
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| _version_ | 1796762724819009536 |
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| author | Satpathy, Rabinarayan, editor 636906 Choudhury, Tanupriya, editor 636907 Satpathy, Suneeta, editor 636908 Mohanty, Sachi Nandan, editor 636909 Zhang, Xiaobo, editor 636874 |
| author_facet | Satpathy, Rabinarayan, editor 636906 Choudhury, Tanupriya, editor 636907 Satpathy, Suneeta, editor 636908 Mohanty, Sachi Nandan, editor 636909 Zhang, Xiaobo, editor 636874 |
| author_sort | Satpathy, Rabinarayan, editor 636906 |
| collection | OCEAN |
| description | "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"-- |
| first_indexed | 2024-03-05T16:45:06Z |
| format | text |
| id | KOHA-OAI-TEST:593207 |
| institution | Universiti Teknologi Malaysia - OCEAN |
| language | eng |
| last_indexed | 2024-04-17T03:12:32Z |
| publishDate | 2021 |
| publisher | Hoboken, NJ : Wiley-Scrivener, |
| record_format | dspace |
| spelling | KOHA-OAI-TEST:5932072024-04-16T04:32:27ZData Analytics in Bioinformatics : A Machine Learning Perspective / Satpathy, Rabinarayan, editor 636906 Choudhury, Tanupriya, editor 636907 Satpathy, Suneeta, editor 636908 Mohanty, Sachi Nandan, editor 636909 Zhang, Xiaobo, editor 636874 textHoboken, NJ : Wiley-Scrivener,2021eng"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"--Includes bibliographical references and index"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"--BioinformaticsArtificial intelligenceURN:ISBN:9781119785538 |
| spellingShingle | Bioinformatics Artificial intelligence Satpathy, Rabinarayan, editor 636906 Choudhury, Tanupriya, editor 636907 Satpathy, Suneeta, editor 636908 Mohanty, Sachi Nandan, editor 636909 Zhang, Xiaobo, editor 636874 Data Analytics in Bioinformatics : A Machine Learning Perspective / |
| title | Data Analytics in Bioinformatics : A Machine Learning Perspective / |
| title_full | Data Analytics in Bioinformatics : A Machine Learning Perspective / |
| title_fullStr | Data Analytics in Bioinformatics : A Machine Learning Perspective / |
| title_full_unstemmed | Data Analytics in Bioinformatics : A Machine Learning Perspective / |
| title_short | Data Analytics in Bioinformatics : A Machine Learning Perspective / |
| title_sort | data analytics in bioinformatics a machine learning perspective |
| topic | Bioinformatics Artificial intelligence |
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