An introduction to the use of DNA microarrays in functional genomics.

This book presents an overview of the state-of-the-art in barley genome analysis, covering all aspects of sequencing the genome and translating this important information into new knowledge in basic and applied crop plant biology and new tools for research and crop improvement. Unlimited access to a high-quality reference sequence is removing one of the major constraints in basic and applied research. This book summarizes the advanced knowledge of the composition of the barley genome, its genes and the much larger non-coding part of the genome, and how this information facilitates studying the specific characteristics of barley. One of the oldest domesticated crops, barley is the small grain cereal species that is best adapted to the highest altitudes and latitudes, and it exhibits the greatest tolerance to most abiotic stresses. With comprehensive access to the genome sequence, barley’s importance as a genetic model in comparative studies on crop species like wheat, rye, oats and even rice is likely to increase.

Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.

This textbook describes recent advances in genomics and bioinformatics and provides numerous examples of genome data analysis that illustrate its relevance to real world problems and will improve the reader’s bioinformatics skills. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine learning algorithms using R and Python are demonstrated for gene-expression microarrays, genotyping microarrays, next-generation sequencing data, epigenomic data, and biological network and semantic analyses. In addition, detailed attention is devoted to integrative genomic data analysis, including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and integrated management of biomolecular databases. The textbook is primarily intended for life scientists, medical scientists, statisticians, data processing researchers, engineers, and other beginners in bioinformatics who are experiencing difficulty in approaching the field. However, it will also serve as a simple guideline for experts unfamiliar with the new, developing subfield of genomic analysis within bioinformatics.

Considered highly exotic tools as recently as the late 1990s, microarrays are now ubiquitous in biological research. Traditional statistical approaches to design and analysis were not developed to handle the high-dimensional, small sample problems posed by microarrays. In just a few short years the number of statistical papers providing approaches

Concise, 2002 inter-disciplinary introduction to DNA microarray technology, which is revolutionizing biology and medicine.

This work is a comprehensive collection of articles that cover aspects of cell wall research in the genomic era. Some 2500 genes are involved in some way in wall biogenesis and turnover, from generation of substrates, to polysaccharide and lignin synthesis, assembly, and rearrangement in the wall. Although a great number of genes and gene families remain to be characterized, this issue provides a census of the genes that have been discovered so far. The articles comprising this issue not only illustrate the enormous progress made in identifying the wealth of wall-related genes but they also show the future directions and how far we have to go. As cell walls are an enormously important source of raw material, we anticipate that cell-wall-related genes are of significant economic importance. Examples include the modification of pectin-cross-linking or cell-cell adhesion to increase shelf life of fruits and vegetables, the enhancement of dietary fiber contents of cereals, the improvement of yield and quality of fibers, and the relative allocation of carbon to wall biomass for use as biofuels. The book is intended for academic and professional scientists working in the area of plant biology as well as material chemists and engineers, and food scientists who define new ways to use cell walls.

This book summarizes the current state of knowledge concerning bacteria that use halogenated organic compounds as respiratory electron acceptors. The discovery of organohalide-respiring bacteria has expanded the range of electron acceptors used for energy conservation, and serves as a prime example of how scientific discoveries are enabling innovative engineering solutions that have transformed remediation practice. Individual chapters provide in-depth background information on the discovery, isolation, phylogeny, biochemistry, genomic features, and ecology of individual organohalide-respiring genera, including Dehalococcoides, Dehalogenimonas, Dehalobacter, Desulfitobacterium and Sulfurospirillum, as well as organohalide-respiring members of the Deltaproteobacteria. The book introduces readers to the fascinating biology of organohalide-respiring bacteria, offering a valuable resource for students, engineers and practitioners alike.