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Next Generation Microarray Bioinformatics

move away from microarray-based technology to ultra high-throughput, massively parallel genomic sequencing (Next Generation Sequencing, NGS;

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Microarray Bioinformatics

This book is a comprehensive guide to all of the mathematics, statistics and computing you will need to successfully operate DNA microarray;

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Microarray Bioinformatics

This book provides a comprehensive, interdisciplinary collection of the main, up-to-date methods, tools, and techniques for microarray data;

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Applications Of Fuzzy Logic In Bioinformatics

structure prediction/analysis, and microarray data analysis. It also reviews other bioinformatics applications using fuzzy techniques.;

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Computational Systems Bioinformatics (Volume 7) - Proceedings Of The Csb 2008 Conference

transcriptome, structural bioinformatics, microarray data analysis, motif identification, biological pathways and systems, and biomedical;

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Bioinformatics and Computational Biology

Representation, Microarray, Sequencing, Alignment, and Related Bioinformatics Issues Computational Biology and Medical Applications + Health;

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Computational Systems Bioinformatics - Proceedings Of The Conference Csb 2006

transcriptome, structural bioinformatics, microarray data analysis, motif identification, biological pathways and systems, and biomedical applications;

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Computational Systems Bioinformatics (Volume 6) - Proceedings Of The Conference Csb 2007

transcriptome, structural bioinformatics, microarray data analysis, motif identification, biological pathways and systems, and biomedical applications;

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Exploration and Analysis of DNA Microarray and Other High-Dimensional Data

of Environmental Quality Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition provides comprehensive coverage;

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A Practical Approach to Microarray Data Analysis

The book addresses the requirement of scientists and researchers to gain a basic understanding of microarray analysis methodologies and;

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Statistics For Microarrays

Interest in microarrays has increased considerably in the last ten years. This increase in the use of microarray technology has led to the;

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Methods of Microarray Data Analysis II

Microarray technology is a major experimental tool for functional genomic explorations, and will continue to be a major tool throughout;

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Data Analytics in Bioinformatics

selection, dimensionality reduction, gene selection and classification of microarray data and many more.;

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Evolutionary Computation Machine Learning and Data Mining in Bioinformatics

, uxomics, gene networks, biotechnology, metabolomics, microarray analysis, phylogenetics, protein interactions, proteomics, sequence analysis and;

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Computational Methods With Applications in Bioinformatics Analysis

, biomolecular interaction, time-series microarray analysis, and machine learning algorithms.The salient feature of this book is that it highlights eight;

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Modeling Dose-response Microarray Data in Early Drug Development Experiments Using R

This book focuses on the analysis of dose-response microarray data in pharmaceutical settings, the goal being to cover this important topic;

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Advances In Bioinformatics And Its Applications - Proceedings Of The International Conference

research papers and state-of-the-art survey articles, the book has been divided into five main sections: Microarray Analysis and Regulatory;

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Gene Expression Studies Using Affymetrix Microarrays

The Affymetrix GeneChip (R) system is one of the most widely adapted microarray platforms. However, due to the overwhelming amount;

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Gene Expression Studies Using Affymetrix Microarrays

The Affymetrix GeneChip (R) system is one of the most widely adapted microarray platforms. However, due to the overwhelming amount;

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Bioinformatics

, phylogenetics analysis, and SNP and haplotype analysis. After chapters on microarray, SAGE, regulation of gene expression, miRNA, and siRNA, the book;

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Bayesian Modeling in Bioinformatics

presents a broad overview of statistical inference, clustering, and classification problems in two main high-throughput platforms: microarray gene;

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Bayesian Modeling in Bioinformatics

presents a broad overview of statistical inference, clustering, and classification problems in two main high-throughput platforms: microarray gene;

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Bioinformatics Database Systems

pathway databases, microarray databases and boutique databases. It also explores the data quality and information integration issues currently;

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Bioinformatics Database Systems

pathway databases, microarray databases and boutique databases. It also explores the data quality and information integration issues currently;

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Machine Learning in Bioinformatics

proteomic data mining; comparing variable selection methods in gene selection and classification of microarray data; fuzzy gene mining; sequence;

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Bioinformatics: A Practical Approach

, phylogenetics analysis, and SNP and haplotype analysis. After chapters on microarray, SAGE, regulation of gene expression, miRNA, and siRNA, the book;

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Computational Systems Bioinformatics - Methods And Biomedical Applications

bioinformatics technology in microarray and sequence analysis step-by-step. Offering an insightful look into the effectiveness of the systems approach;

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