Application of Bioinformatics in Cancers
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
eBook, Undefined, 2019
MDPI - Multidisciplinary Digital Publishing Institute, [Erscheinungsort nicht ermittelbar], 2019
1 Online-Ressource (1 electronic resource (418 p.))
9783039217885, 9783039217892, 3039217887, 3039217895
1193021991
English
www.doabooks.org Description of rights in Directory of Open Access Books (DOAB): Attribution Non-commercial No Derivatives (CC by-nc-nd) kostenfrei