Microarray Image Analysis

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A01=Karl Fraser
A01=Xiaohui Liu
A01=Zidong Wang
Author_Karl Fraser
Author_Xiaohui Liu
Author_Zidong Wang
automated microarray data interpretation
background
biomedical image processing
block
Category=PS
clustering
clustering methods in genomics
Complementary Deoxyribonucleic Acid
computational biology
Control Spots
Data Sets
DNA microarray technology
EM algorithm
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
expectation maximization algorithm
expression
feature extraction techniques
feature identification
gene
gene expression analysis
Gene Expression Data
gene expression data mining
Gene Expression Ratios
Gene Expression Time Series
Gene Expression Time Series Data
Gene Regulatory Networks
Gene Spots
GHT
graph-cutting
Image Region
Image Surface
Left Image
local
master
Master Block
Microarray Analysis
Microarray Field
Microarray Image
Microarray Image Analysis
microarray image processing
Microarray Technology
Middle Image
Reconstruction Techniques
region
regulatory
SB
ScoreCard Genes
spots
stochastic dynamic model
structure extrapolation
subgrid detection
surface
time series
Traditional Clustering Methods
Traditional Clustering Techniques

Product details

  • ISBN 9781138115156
  • Weight: 620g
  • Dimensions: 156 x 234mm
  • Publication Date: 14 Jun 2017
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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To harness the high-throughput potential of DNA microarray technology, it is crucial that the analysis stages of the process are decoupled from the requirements of operator assistance. Microarray Image Analysis: An Algorithmic Approach presents an automatic system for microarray image processing to make this decoupling a reality. The proposed system integrates and extends traditional analytical-based methods and custom-designed novel algorithms.

The book first explores a new technique that takes advantage of a multiview approach to image analysis and addresses the challenges of applying powerful traditional techniques, such as clustering, to full-scale microarray experiments. It then presents an effective feature identification approach, an innovative technique that renders highly detailed surface models, a new approach to subgrid detection, a novel technique for the background removal process, and a useful technique for removing "noise." The authors also develop an expectation–maximization (EM) algorithm for modeling gene regulatory networks from gene expression time series data. The final chapter describes the overall benefits of these techniques in the biological and computer sciences and reviews future research topics.

This book systematically brings together the fields of image processing, data analysis, and molecular biology to advance the state of the art in this important area. Although the text focuses on improving the processes involved in the analysis of microarray image data, the methods discussed can be applied to a broad range of medical and computer vision analysis areas.

Karl Fraser is a research fellow in the Centre for Intelligent Data Analysis at Brunel University.

Zidong Wang is a professor of dynamical systems and computing in the Department of Information Systems and Computing at Brunel University.

Xiaohu Liu is a professor of computing and head of the Centre for Intelligent Data Analysis at Brunel University.

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