logo
Product categories

EbookNice.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link.  https://ebooknice.com/page/post?id=faq


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookNice Team

(Ebook) Data Analytics in Bioinformatics: A Machine Learning Perspective by Rabinarayan Satpathy (editor), Tanupriya Choudhury (editor), Suneeta Satpathy (editor), Sachi Nandan Mohanty (editor), Xiaobo Zhang (editor) ISBN 9781119785538, 1119785537

  • SKU: EBN-36137846
Zoomable Image
$ 32 $ 40 (-20%)

Status:

Available

4.7

10 reviews
Instant download (eBook) Data Analytics in Bioinformatics: A Machine Learning Perspective after payment.
Authors:Rabinarayan Satpathy (editor), Tanupriya Choudhury (editor), Suneeta Satpathy (editor), Sachi Nandan Mohanty (editor), Xiaobo Zhang (editor)
Pages:544 pages.
Year:2021
Editon:1
Publisher:Wiley-Scrivener
Language:english
File Size:16.64 MB
Format:pdf
ISBNS:9781119785538, 1119785537
Categories: Ebooks

Product desciption

(Ebook) Data Analytics in Bioinformatics: A Machine Learning Perspective by Rabinarayan Satpathy (editor), Tanupriya Choudhury (editor), Suneeta Satpathy (editor), Sachi Nandan Mohanty (editor), Xiaobo Zhang (editor) ISBN 9781119785538, 1119785537

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.
*Free conversion of into popular formats such as PDF, DOCX, DOC, AZW, EPUB, and MOBI after payment.

Related Products