Semi-Markov Chains and Hidden Semi-Markov Models toward Applications: Their Use in Reliability and DNA Analysis

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This book is concerned with the estimation of discrete-time semi-Markov and hidden semi-Markov processes. Semi-Markov processes are much more general and better adapted to applications than the Markov ones because sojourn times in any state can be arbitrarily distributed, as opposed to the geometrically distributed sojourn time in the Markov case. Another unique feature of the book is the use of discrete time, especially useful in some specific applications where the time scale is intrinsically discrete. The models presented in the book are specifically adapted to reliability studies and DNA analysis.

The book is mainly intended for applied probabilists and statisticians interested in semi-Markov chains theory, reliability and DNA analysis, and for theoretical oriented reliability and bioinformatics engineers. It can also serve as a text for a six month research-oriented course at a Master or PhD level. The prerequisites are a background in probability theory and finite state space Markov chains.

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Introduction to Machine Learning and Bioinformatics

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Lucidly Integrates Current Activities

Focusing on both fundamentals and recent advances, Introduction to Machine Learning and Bioinformatics presents an informative and accessible account of the ways in which these two increasingly intertwined areas relate to each other.

Examines Connections between Machine Learning & Bioinformatics

The book begins with a brief historical overview of the technological developments in biology. It then describes the main problems in bioinformatics and the fundamental concepts and algorithms of machine learning. After forming this foundation, the authors explore how machine learning techniques apply to bioinformatics problems, such as electron density map interpretation, biclustering, DNA sequence analysis, and tumor classification. They also include exercises at the end of some chapters and offer supplementary materials on their website.

Explores How Machine Learning Techniques Can Help Solve Bioinformatics Problems

Shedding light on aspects of both machine learning and bioinformatics, this text shows how the innovative tools and techniques of machine learning help extract knowledge from the deluge of information produced by today’s biological experiments.

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Bioinformatics: A Practical Approach

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An emerging, ever-evolving branch of science, bioinformatics has paved the way for the explosive growth in the distribution of biological information to a variety of biological databases, including the National Center for Biotechnology Information. For growth to continue in this field, biologists must obtain basic computer skills while computer specialists must possess a fundamental understanding of biological problems. Bridging the gap between biology and computer science, Bioinformatics: A Practical Approach assimilates current bioinformatics knowledge and tools relevant to the omics age into one cohesive, concise, and self-contained volume.

Written by expert contributors from around the world, this practical book presents the most state-of-the-art bioinformatics applications. The first part focuses on genome analysis, common DNA analysis tools, phylogenetics analysis, and SNP and haplotype analysis. After chapters on microarray, SAGE, regulation of gene expression, miRNA, and siRNA, the book presents widely applied programs and tools in proteome analysis, protein sequences, protein functions, and functional annotation of proteins in murine models. The last part introduces the programming languages used in biology, website and database design, and the interchange of data between Microsoft Excel and Access.

Keeping complex mathematical deductions and jargon to a minimum, this accessible book offers both the theoretical underpinnings and practical applications of bioinformatics.

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imaGenes GmbH passes certification process to qualify as Roche NimbleGen CSP for DNA Methylation Analysis

imaGenes GmbH passes certification process to qualify as Roche NimbleGen CSP for DNA Methylation Analysis
Roche NimbleGen is pleased to announce that imaGenes GmbH, located in Berlin, Germany, has passed the certification process to qualify as a Roche NimbleGen Certified Service Provider for DNA Methylation Analysis. imaGenes is a solution provider for functional genomics and proteomics with a comprehensive portfolio of high-quality services for molecular life sciences.

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imaGenes GmbH Adds Certification of Roche NimbleGen DNA Methylation Analysis to Service Portfolio

imaGenes GmbH Adds Certification of Roche NimbleGen DNA Methylation Analysis to Service Portfolio
MADISON, Wis.—-Roche NimbleGen is pleased to announce that imaGenes GmbH, located in Berlin, Germany, has passed the certification process to qualify as a Roche NimbleGen Certified Service Provider for DNA Methylation Analysis. imaGenes is a solution provider for functional genomics and proteomics with a comprehensive portfolio of high-quality services for molecular life sciences.

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