Can I read Big Data Bioinformatics: BIG DATA BIOINFORMATICS on EtoBox?

Big Data Bioinformatics: BIG DATA BIOINFORMATICS by Casey S. Greene; Jie Tan; Matthew Ung; Jason H. Moore; Chao Cheng is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

What is Big Data Bioinformatics: BIG DATA BIOINFORMATICS about?

Recent technological advances allow for high throughput profiling of biological systems in a cost-efficient manner. The low cost of data generation is leading us to the "big data" era. The availability of big data provides unprecedented opportunities but also raises new challenges for data mining and analysis. In this review, we introduce key concepts in the analysis of big data, including both "machine learning" algorithms as well as "unsupervised" and "supervised" examples of each. We note packages for the R programming language that are available to perform machine learning analyses. In addition to programming based solutions, we review webservers that allow users with limited or no programming background to perform these analyses on large data compendia.

Who reads Big Data Bioinformatics: BIG DATA BIOINFORMATICS?

Author

Casey S. Greene; Jie Tan; Matthew Ung; Jason H. Moore; Chao Cheng

Publisher

John Wiley and Sons; Wiley (John Wiley & Sons); John Wiley & Sons Inc.; Wiley (ISSN 0021-9541)

Published

2014

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)