ABSTRACT

Proven Methods for Big Data Analysis

As big data has become standard in many application areas, challenges have arisen related to methodology and software development, including how to discover meaningful patterns in the vast amounts of data. Addressing these problems, Applied Biclustering Methods for Big and High-Dimensional Data Using R shows how to apply biclustering methods to find local patterns in a big data matrix.

The book presents an overview of data analysis using biclustering methods from a practical point of view. Real case studies in drug discovery, genetics, marketing research, biology, toxicity, and sports illustrate the use of several biclustering methods. References to technical details of the methods are provided for readers who wish to investigate the full theoretical background. All the methods are accompanied with R examples that show how to conduct the analyses. The examples, software, and other materials are available on a supplementary website.

chapter 1|10 pages

Introduction

ByZiv Shkedy, Adetayo Kasim, Sepp Hochreiter, Sebastian Kaiser, Willem Talloen

chapter 2|24 pages

From Cluster Analysis to Biclustering

part |2 pages

I Biclustering Methods

chapter 3|12 pages

δ-Biclustering and FLOC Algorithm

chapter 4|12 pages

The xMotif algorithm

chapter 5|12 pages

Bimax Algorithm

chapter 6|16 pages

The Plaid Model

ByZiv Shkedy, Ewoud De Troyer, Adetayo Kasim, Sepp Hochreiter, Heather Turner

chapter 7|10 pages

Spectral Biclustering

chapter 8|20 pages

FABIA

BySepp Hochreiter

chapter 9|12 pages

Iterative Signature Algorithm

chapter 10|26 pages

Ensemble Methods and Robust Solutions

ByTatsiana Khamiakova, Sebastian Kasier, Ziv Shkedy

part |2 pages

II Case Studies and Applications

chapter 13|10 pages

Integrative Analysis of miRNA and mRNA Data

chapter 17|16 pages

Overcoming Data Dimensionality Problems in Market Seg- mentation

BySebastian Kaiser, Sara Dolnicar, Katie Lazarevski, Friedrich Leisch

chapter 19|22 pages

Identification of Local Patterns in the NBA Performance In- dicators

ByZiv Shkedy, Rudradev Sengupta, Nolen Joy Perualila

part |2 pages

III R Tools for Biclustering

chapter 20|28 pages

The BiclustGUI Package

chapter 21|14 pages

We R a Community - Including a New Package in BiclustGUI

ByEwoud De Troyer

chapter 22|10 pages

Biclustering for Cloud Computing

chapter 23|12 pages

biclustGUI Shiny App