Application of Bioinformatics in Cancers

Application of Bioinformatics in Cancers

Cancer

This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible.

Brenner, J. Chad

https://directory.doabooks.org/handle/20.500.12854/41042

MDPI - Multidisciplinary Digital Publishing Institute

2017

Dewi Puspitasari

https://creativecommons.org/licenses/by-nc-nd/4.0/

International Agency for Research on Cancer. Available online: https://gco.iarc.fr/ (accessed on 1 November 2018).

Pdf

English

Textbooks

DOI
10.3390/books978-3-03921-789-2

ISBN
9783039217892, 9783039217885

Basel