Computational and statistical methodologies for data mining in bioinformatics

1Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The aims of this chapter are to provide an overview of the high-throughput technologies currently available, with particular focus on genomic and pro-teomic analyses of biological samples. Further, a non-mathematical overview of the statistical and computational methods that are available for the analysis and subsequent data mining of these data will be discussed, together with an outline of the careful considerations that have to be made prior to these analyses. Given that the literature is vast within the area of computational biology, we seek to present an overview of some of the most commonly used methods. Additionally, apart from describing the methods, we will illustrate selected examples with results from our own studies using real data sets. © Springer-Verlag Berlin Heidelberg 2010.

Cite

CITATION STYLE

APA

Lancashire, L., & Ball, G. (2010). Computational and statistical methodologies for data mining in bioinformatics. In Key Topics in Surgical Research and Methodology (pp. 337–350). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-71915-1_27

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free