Articles liés à Computational Analysis of SAGE Data: Data Mining Approach

Computational Analysis of SAGE Data: Data Mining Approach - Couverture souple

K.R., Seeja

 
9783659201417: Computational Analysis of SAGE Data: Data Mining Approach

Synopsis

In post genomic era, with the availability of the large number of genome databases the focus of research has shifted from sequencing to eliciting knowledge from these databases. Data mining is a collection of techniques for discovering previously unknown, valid and useful patterns from large databases. This book gives insight into an application of a data mining technique, called association rule mining, in analyzing Serial Analysis of Gene Expression (SAGE) data. SAGE is a sequencing technique used for measuring the expression levels of genes. Traditional association rule mining algorithms are not suitable for mining gene expression data due to its wide structure. This book contains the description of a specialized association rule mining algorithm, called GeneExpMiner, for SAGE Data analysis. It also contains an application of the association rule mining, where the algorithm is applied to SAGE data, for identifying the co-regulated signature genes. Some open problems which can be considered for further research in this area is also provided at the conclusion. This book is intended to research scholars in the area of computational biology or bioinformatics.

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Présentation de l'éditeur

In post genomic era, with the availability of the large number of genome databases the focus of research has shifted from sequencing to eliciting knowledge from these databases. Data mining is a collection of techniques for discovering previously unknown, valid and useful patterns from large databases. This book gives insight into an application of a data mining technique, called association rule mining, in analyzing Serial Analysis of Gene Expression (SAGE) data. SAGE is a sequencing technique used for measuring the expression levels of genes. Traditional association rule mining algorithms are not suitable for mining gene expression data due to its wide structure. This book contains the description of a specialized association rule mining algorithm, called GeneExpMiner, for SAGE Data analysis. It also contains an application of the association rule mining, where the algorithm is applied to SAGE data, for identifying the co-regulated signature genes. Some open problems which can be considered for further research in this area is also provided at the conclusion. This book is intended to research scholars in the area of computational biology or bioinformatics.

Biographie de l'auteur

The author received B.E and M.E degrees in Computer Engineering and Ph.D.in Computer Science from Jamia Hamdard University, India. Her research areas are Data Mining and Bioinformatics. She has 15 years of teaching experience and currently, she is Assistant Professor in the Department of Computer Science, Jamia Hamdard University, New Delhi, India.

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