High Throughput Genimic Data Analysis

This book shows how to decompose high-dimensional microarrays into small subspaces (Small Matryoshkas, SMs), statistically analyze them, and perform cancer gene diagnosis. The information is useful for genetic experts, anyone who analyzes genetic data, and students to use as practical textbooks.

The ultimate goal of bioinformatics is to extract biological knowledge out of the large amount of information generated by the scientific community. The chapters compiled in this volume will allow both biologists and computer scientists to understand the significance and potential of this discipline in the analysis of high throughput sequencing data.

The ultimate goal of bioinformatics is to extract biological knowledge out of the large amount of information generated by the scientific community. The chapters compiled in this volume will allow both biologists and computer scientists to understand the significance and potential of this discipline in the analysis of high throughput sequencing data.

The ultimate goal of bioinformatics is to extract biological knowledge out of the large amount of information generated by the scientific community. The chapters compiled in this volume will allow both biologists and computer scientists to understand the significance and potential of this discipline in the analysis of high throughput sequencing data. An essential reference book, not only for serving as guideline for the comprehension of the main data analysis steps, but also for providing new insights into existing software and inspiration to develop new applications.