Microarray data analysis of M.tuberculosis whole genome using Genesis | Cluster Analysis and Co-expression study of Mycobacterium tuberculosis for Genome Wide Microarray Expression Data

Utkarsh Raj (u. a.)

ISBN 10: 3659185167 / ISBN 13: 9783659185168

Published by LAP LAMBERT Academic Publishing, 2012

About this Item

Microarray data analysis of M.tuberculosis whole genome using Genesis | Cluster Analysis and Co-expression study of Mycobacterium tuberculosis for Genome Wide Microarray Expression Data | Utkarsh Raj (u. a.) | Taschenbuch | 56 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783659185168 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Seller Inventory # 106376611

Bibliographic Details

• Title: Microarray data analysis of M.tuberculosis whole genome using Genesis | Cluster Analysis and Co-expression study of Mycobacterium tuberculosis for Genome Wide Microarray Expression Data
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2012
• Language: English
• ISBN 10: 3659185167
• ISBN 13: 9783659185168
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 4D millimeters 220 millimeters width by 150 millimeters height by 4 millimeters depth
• Weight: 102 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

DNA microarrays are a powerful tool to investigate differential gene expression for thousands of genes simultaneously. Although DNA microarrays have been widely used to understand the critical events underlying growth, development, homeostasis, behavior and the onset of disease, the management of the resulting data has received little attention. Presently, the fluorescent dyes Cy3 and Cy5 are most often used to prepare labeled cDNA for microarray hybridizations. Raw microarray data are image files that have to be transformed into gene expression formats – a process that requires data manipulation due to systematic variations which may be attributed to differences in the physical and chemical dye characteristics. There are different approaches to analyse the large-scale gene expression data in which the essence is to identify gene clusters. This approach has allowed us to determine expression profiles of novel developmentally regulated genes. Finally we get some genes which highly coexpressed and may be involved in pathogenesis.

About the Author

I am pursuing M.Tech (Biotechnology) from Gautam Buddha University, India. My area of interest is Bioinformatics mainly CADD, Protein Modelling, Microarray Analysis, Web designing etc. I had done various projects which got accepted at National/International level.I am also thankful to Ms.Naina, for being there throughout this project to support me.