After genomic sequencing, microarray technology has emerged as a widely used platform for genomic studies in the life sciences. Microarray technology provides a systematic way to survey DNA and RNA variation. With the abundance of data produced from microarray studies, however, the ultimate impact of the studies on biology will depend heavily on data mining and statistical analysis. The contribution of this book is to provide readers with an integrated presentation of various topics on analyzing microarray data.

Genetic recombination, in the broadest sense, can be defined as any process in which DNA sequences interact and undergo a transfer of information, producing new "recombinant" sequences that contain information from each of the original molecules. All organisms have the ability to carry out recombination, and this striking universality speaks to the essential role recombination plays in a variety of biological processes fundamentally important to the maintenance of life. Such processes include DNA repair, regulation of gene expression, disease etiology, meiotic chromosome segregation, and evolution. One important aspect of recombination is that it typically occurs only between sequences that display a high degree of sequence identity. The stringent requirement for homology helps to ensure that, under normal circumstances, a cell is protected from deleterious rearrangements since a swap of genetic information between two nearly identical sequences is not expected to dramatically alter a genome. Recombination between dissimilar sequences, which does happen on occasion, may have such harmful consequences as chromosomal translocations, deletions, or inversions. For many organisms, it is also important that recombination rates are not too high lest the genome become destabilized. Curiously, certain organisms, such as the trypanosome parasite, actually use a high rate of recombination at a particular locus in order to switch antigen expression continually and evade the host immune system effectively.

Bioinformatics of Genome Regulation and Structure covers:

-regulatory genomic sequences: databases, knowledge bases, computer analysis, modeling, and recognition;
-large-scale genome analysis and functional annotation;
-gene structure detection and prediction;
-comparative and evolutionary genomics;
-computer analysis of genome polymorphism and evolution; computer analysis and modeling of transcription, splicing, and translation; structural computational biology: structure-function organization of genomic DNA, RNA, and proteins;
-gene networks, signal transduction pathways, and genetically controlled metabolic pathways: principles of organization, operation, and evolution;
-data warehousing, knowledge discovery and data mining; and,
-analysis of basic patterns of genome operation, organization, and evolution. The data presented may be used while solving a wide range of problems, both basic and applied, in various directions of molecular biology, molecular genetics, biotechnology, pharmacogenetics, pharmacology, and adjacent fields of medicine, veterinary, and agrobiology.

The functional properties of any molecule are directly related to, and affected by, its structure. This is especially true for DNA, the molecular that carries the code for all life on earth.
The third edition of Understanding DNA has been entirely revised and updated, and expanded to cover new advances in our understanding. It explains, step by step, how DNA forms specific structures, the nature of these structures and how they fundamentally affect the biological processes of transcription and replication.
Written in a clear, concise and lively fashion, Understanding DNA is essential reading for all molecular biology, biochemistry and genetics students, to newcomers to the field from other areas such as chemistry or physics, and even for seasoned researchers, who really want to understand DNA.
* Describes the basic units of DNA and how these form the double helix, and the various types of DNA double helix
* Outlines the methods used to study DNA structure
* Contains over 130 illustrations, some in full color, as well as exercises and further readings to stimulate student comprehension

As microarray technology has matured, data analysis methods have advanced as well. Methods Of Microarray Data Analysis III is the third book in this pioneering series dedicated to the existing new field of microarrays. While initial techniques focused on classification exercises (volume I of this series), and later on pattern extraction (volume II of this series), this volume focuses on data quality issues. Problems such as background noise determination, analysis of variance, and errors in data handling are highlighted.

Three tutorial papers are presented to assist with a basic understanding of underlying principles in microarray data analysis, and twelve new papers are highlighted analyzing the same CAMDA'02 datasets: the Project Normal data set or the Affymetrix Latin Square data set. A comparative study of these analytical methodologies brings to light problems, solutions and new ideas. This book is an excellent reference for academic and industrial researchers who want to keep abreast of the state of art of microarray data analysis.

A Beginner's Guide to Microarrays addresses two audiences - the core facility manager who produces, hybridizes, and scans arrays, and the basic research scientist who will be performing the analysis and interpreting the results. User friendly coverage and detailed protocols are provided for the technical steps and procedures involved in many facets of microarray technology, including:

-Cleaning and coating glass slides,
-Designing oligonucleotide probes,
-Constructing arrays for the detection and quantification of different bacterial species,
-Preparing spotting solutions,
-Troubleshooting spotting problems,
-Setting up and running a core facility,
-Normalizing background signal and controlling for systematic variance,
-Designing experiments for maximum effect,
-Analyzing data with statistical procedures,
-Clustering data with machine-learning protocols.

At present, there is growing interest in high pressure bioscience and biotechnology. The activities are nearly equally distributed between fundamental research and applications. With original work on marine and terrestrial microbiology, biochemistry, molecular biology, deep-sea diving, food science and other industrial applications, this book covers the whole range of current high pressure bioscience. Advances in High Pressure Bioscience and Biotechnology will be welcomed by all industrial and academic researchers who are working in this field.

This book presents practical approaches for the analysis of data from gene expression microarrays. Each chapter describes the conceptual and methodological underpinning for a statistical tool and its implementation in software. Methods cover all aspects of statistical analysis of microarrays, from annotation and filtering to clustering and classification. Chapters are written by the developers of the software. All software packages described are free to academic users. The book includes coverage of various packages that are part of the Bioconductor project and several related R tools. The materials presented cover a range of software tools designed for varied audiences. Some chapters describe simple menu-driven software in a user-friendly fashion, and are designed to be accessible to microarray data analysts without formal quantitative training. Most chapters are directed at microarray data analysts with master-level training in computer science, biostatistics or bioinformatics. A minority of more advanced chapters are intended for doctoral students and researchers. The team of editors is from the Johns Hopkins Schools of Medicine and Public Health and has been involved with developing methods and software for microarray data analysis since the inception of this technology. Giovanni Parmigiani is Associate Professor of Oncology, Pathology and Biostatistics. He is the author of the book on "Modeling in Medical decision Making," a fellow of the ASA, and a recipient of the Savage Awards for Bayesian statistics. Elizabeth S. Garrett is Assistant Professor of Oncology and Biostatistics, and recipient of the Abbey Award for statistical education. Rafael A Irizarry is Assistant Professor of Biostatistics, and recipient of the Noether Award for non-parametric statistics. Scott L. Zeger is Professor and chair of Biostatistics. He is co-author of the book "Longitudinal Data Analysis," a fellow of the ASA and recipient of the Spiegelman Award for public health statistics.

Directed evolution comprises two distinct steps that are typically applied in an iterative fashion: (1) generating molecular diversity and (2) finding among the ensemble of mutant sequences those proteins that perform the desired fu- tion according to the specified criteria. In many ways, the second step is the most challenging. No matter how cleverly designed or diverse the starting library, without an effective screening strategy the ability to isolate useful clones is severely diminished. The best screens are (1) high throughput, to increase the likelihood that useful clones will be found; (2) sufficiently sen- tive (i. e. , good signal to noise) to allow the isolation of lower activity clones early in evolution; (3) sufficiently reproducible to allow one to find small improvements; (4) robust, which means that the signal afforded by active clones is not dependent on difficult-to-control environmental variables; and, most importantly, (5) sensitive to the desired function. Regarding this last point, almost anyone who has attempted a directed evolution experiment has learned firsthand the truth of the dictum "you get what you screen for. " The protocols in Directed Enzyme Evolution describe a series of detailed p- cedures of proven utility for directed evolution purposes. The volume begins with several selection strategies for enzyme evolution and continues with assay methods that can be used to screen enzyme libraries. Genetic selections offer the advantage that functional proteins can be isolated from very large libraries s- ply by growing a population of cells under selective conditions.

This book contains articles written by experts on a wide range of topics that are associated with the analysis and management of biological information at the molecular level. It contains chapters on RNA and protein structure analysis, DNA computing, sequence mapping, genome comparison, gene expression data mining, metabolic network modeling, and phyloinformatics. The important work of some representative researchers in bioinformatics is brought together for the first time in one volume. The topic is treated in depth and is related to, where applicable, other emerging technologies such as data mining and visualization. The goal of the book is to introduce readers to the principle techniques of bioinformatics in the hope that they will build on them to make new discoveries of their own. Contents: Exploring RNA Intermediate Conformations with the Massively Parallel Genetic Algorithm; Introduction to Self-Assembling DNA Nanostructures for Computation and Nanofabrication; Mapping Sequence to Rice FPC; Graph Theoretic Sequence Clustering Algorithms and their Applications to Genome Comparison; The Protein Information Resource for Functional Genomics and Proteomics; High-Grade Ore for Data Mining in 3D Structures; Protein Classification: A Geometric Hashing Approach; Interrelated Clustering: An Approach for Gene Expression Data Analysis; Creating Metabolic Network Models Using Text Mining and Expert Knowledge; Phyloinformatics and Tree Networks. Readership: Molecular biologists who rely on computers and mathematical scientists with interests in biology.

The recent progress achieved in aquatic genomics research has important implications in science and aquaculture. Researchers' success in genome sequencing of the fugu has provided a foundation not only for comparative fish genomics but also for genetic studies of other vertebrates. This volume, with contributions by leading scientists from around the world, provides the latest information on genomic studies of a variety of aquatic organisms including fish, crustaceans, and shellfish, with descriptions of such methodologies as genome analysis, gene mapping, DNA markers, and EST analysis. Other topics include regulation of gene expression, stress and immune responses, sex differentiation, hormonal control, and transgenic fish. This book is a valuable resource for all scientists whose work involves aquatic organisms, especially for those in the fields of aquatic genomics, fish immunology, and aquatic biotechnology.

In the past several years, DNA microarray technology has attracted tremendous interest in both the scientific community and in industry. With its ability to simultaneously measure the activity and interactions of thousands of genes, this modern technology promises unprecedented new insights into mechanisms of living systems. Currently, the primary applications of microarrays include gene discovery, disease diagnosis and prognosis, drug discovery (pharmacogenomics), and toxicological research (toxicogenomics). Typical scientific tasks addressed by microarray experiments include the identification of coexpressed genes, discovery of sample or gene groups with similar expression patterns, identification of genes whose expression patterns are highly differentiating with respect to a set of discerned biological entities (e.g., tumor types), and the study of gene activity patterns under various stress conditions (e.g., chemical treatment). More recently, the discovery, modeling, and simulation of regulatory gene networks, and the mapping of expression data to metabolic pathways and chromosome locations have been added to the list of scientific tasks that are being tackled by microarray technology. Each scientific task corresponds to one or more so-called data analysis tasks. Different types of scientific questions require different sets of data analytical techniques. Broadly speaking, there are two classes of elementary data analysis tasks, predictive modeling and pattern-detection. Predictive modeling tasks are concerned with learning a classification or estimation function, whereas pattern-detection methods screen the available data for interesting, previously unknown regularities or relationships.

Sequence - Evolution - Function is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis.

Key topics covered in this textbook are:
*the completed and ongoing genome sequencing projects,
*databases that store and organize genomic data, with their unique advantages and pitfalls,
*principles and methods of genome analysis and annotation,
*ways to automate the searches and increase search sensitivity while minimizing the error rate,
*the first lessons from the Human Genome Project,
*the contribution of comparative genomics to the understanding of hereditary diseases and cancer,
*fundamental and practical applications of comparative genomics,
*the use of complete genomes for evolutionary analysis,
*the application of comparative genomics for identification of potential drug targets in microbial genomes,
*Problems for Further Study, which are designed to be solved by using methods available through the WWW. Sequence - Evolution - Function should help bridge the "digital divide" between biologists and computer scientists, allowing biologists to better grasp the peculiarities of the emerging field of Genome Biology and to learn how to benefit from the enormous amount of sequence data available in the public databases. The book is non-technical with respect to the computer methods for genome analysis and discusses these methods from the user's viewpoint, without addressing mathematical and algorithmic details. Prior practical familiarity with the basic methods for sequence analysis is a major advantage, but a reader without such experience will be able to use the book as an introduction to these methods. This book is perfect for introductory level courses in computational methods for comparative and functional genomics.

Crick and Watson's discovery of the structure of DNA fifty years ago marked one of the great turning points in the history of science. Biology, immunology, medicine and genetics have all been radically transformed in the succeeding half-century, and the double helix has become an icon of our times. This fascinating exploration of a scientific phenomenon provides a lucid and engaging account of the background and context for the discovery, its significance and afterlife, while a series of essays by leading scientists, historians and commentators offers uniquely individual perspectives on DNA and its impact on modern science and society.

Ancient DNA Typing is a comprehensive manual about the analysis of ancient and degraded DNA. It is an equally useful textbook and working tool for various disciplines such as: Anthropology, Archaeology, Forensic Medicine, Conservation Biology, Environmental Sciences and Food Engineering.The reader benefits from a clear division of strategies, methods and applications with many interesting examples of the analysis of historic skeletal and cultural remains. The book contains a detailed protocol chapter which serves as a lab manual with the most important methods for DNA extraction, PCR and electrophoretic analysis of degraded samples. The appendix helps to set up a PCR lab specializing in ancient DNA research and answers the most frequent questions concerning technical problems in investigations of degraded DNA.

In 1957 two young scientists, Matthew Meselson and Frank Stahl, produced a landmark experiment confirming that DNA replicates as predicted by the double helix structure Watson and Crick had recently proposed. It also gained immediate renown as a "most beautiful" experiment whose beauty was tied to its simplicity. Yet the investigative path that led to the experiment was anything but simple, Frederic L. Holmes shows in this masterful account of Meselson and Stahl's quest. This book vividly reconstructs the complex route that led to the Meselson-Stahl experiment and provides an inside view of day-to-day scientific research--its unpredictability, excitement, intellectual challenge, and serendipitous windfalls, as well as its frustrations, unexpected diversions away from original plans, and chronic uncertainty. Holmes uses research logs, experimental films, correspondence, and interviews with the participants to record the history of Meselson and Stahl's research, from their first thinking about the problem through the publication of their dramatic results. Holmes also reviews the scientific community's reception of the experiment, the experiment's influence on later investigations, and the reasons for its reputation as an exceptionally beautiful experiment.

Bioinformatics is a new and fast expanding area of biology encompassing the organization, analysis and interpretation of the huge amount of data emerging from sequencing and genome projects. Major new programs, software and internet facilities have evolved recently that enable bioinformatic analysis at the whole genome level and more novel technologies are currently being developed. Written by experts in the field, this concise yet informative volume covers all aspects of bioinformatics pertaining to genomic studies. It is an essential book for anyone involved in genomic science or bioinformatics.

Microarray technology is a major experimental tool for functional genomic explorations, and will continue to be a major tool throughout this decade and beyond. The recent explosion of this technology threatens to overwhelm the scientific community with massive quantities of data. Because microarray data analysis is an emerging field, very few analytical models currently exist. Methods of Microarray Data Analysis II is the second book in this pioneering series dedicated to this exciting new field. In a single reference, readers can learn about the most up-to-date methods, ranging from data normalization, feature selection, and discriminative analysis to machine learning techniques.

Currently, there are no standard procedures for the design and analysis of microarray experiments. Methods of Microarray Data Analysis II focuses on a single data set, using a different method of analysis in each chapter. Real examples expose the strengths and weaknesses of each method for a given situation, aimed at helping readers choose appropriate protocols and utilize them for their own data set. In addition, web links are provided to the programs and tools discussed in several chapters. This book is an excellent reference not only for academic and industrial researchers, but also for core bioinformatics/genomics courses in undergraduate and graduate programs.

Eminent scientists have contributed comprehensive reviews on all aspects of the genomics of Rhodococcus, Mycobacteria, Streptomyces and other organisms. The authors provide an insight into the many facets of large scale functional investigation in a variety of bacteria with the explicit goal to find common rules in the dynamic and structural organization of these organisms. This volume is the definitive guide to current research in this increasingly important area and is essential reading for all microbiologists, biotechnologists, and genome scientists.

Genomics is a new and fast expanding area of biology encompassing high throughput or large scale experimentation at the whole genome level, and the organization, analysis and interpretation of the huge amount of data emerging from genome projects. Major new technologies have evolved recently that enable experimentation at the whole genome level, and more novel technologies are currently being developed. This volume describes in detail the new technology necessary to study the entire genome in a holistic manner and all the high throughput and large-scale experimental methodologies currently being used in genomic science. In addition the authors describe the progress of the newest technologies that are currently being developed. Written by experts in the field, this concise yet informative volume covers all aspects of technology pertaining to genomic studies. It is an essential book for anyone involved in genomic science.

DNA Repair and Replication brings together contributions from active researchers. The first part of this book covers most aspects of the DNA damage response, emphasizing the relationship to replication stress. The second part concentrates on the relevance of this to human disease, with particular focus on both the causes and treatments which make use of DNA Damage Repair (DDR) pathways. Key Selling Features: Chapters written by leading researchers Includes description of replication processes, causes of damage, and methods of repair

This volume describes high-throughput approaches to a series of robust, established methodologies in molecular genetic studies of population samples. Such developments have been essential not only to linkage and association studies of single-gene and complex traits in humans, animals and plants, but also to the characterisation of clone banks, for example in mapping of genomes. Chapters have been written by developers or highly experienced end-users concerned with a diverse array of biological applications. The book should appeal to any researcher for whom costs and throughput in their genetics laboratory have become an issue.

This volume describes high-throughput approaches to a series of robust, established methodologies in molecular genetic studies of population samples. Such developments have been essential not only to linkage and association studies of single-gene and complex traits in humans, animals and plants, but also to the characterisation of clone banks, for example in mapping of genomes. Chapters have been written by developers or highly experienced end-users concerned with a diverse array of biological applications. The book should appeal to any researcher for whom costs and throughput in their genetics laboratory have become an issue.

This complete and practical manual on expression measurement using DNA arrays covers the existing methods (from nylon macroarrays to oligonucleotide chips) and includes detailed protocols. It has been written by practising scientists who have experienced the difficulties involved in actually using microarrays, and provides helpful advice and hints on setting up these powerful but sometimes tricky methods. Software, data mining procedures and probable future developments, which should be useful to any practising scientist interested in expression measurement, are also covered in this book. It also provides detailed protocols as well as many helpful hints to achieve experimental success and to avoid pitfalls.

Proteomics is an introduction to the exciting new field of proteomics, an interdisciplinary science that includes biology, bioinformatics, and protein chemistry. The purpose of this book is to provide the active researcher with an overview of the types of questions being addressed in proteomics studies and the technologies used to address those questions. Key subjects covered in this book include: an assessment of the limitations of this approach and outlines new developments in mass spectrometry that will advance future research high-throughput recombinant DNA cloning methods used to systematically clone all of the open reading frames of an organism into plasmid vectors for large scale protein expression and functional studies such as protein-protein interactions with the two-hybrid system protein structure an overview of large-scale experimental attempts to determine the three-dimensional structures of representative sets of proteins computational approaches to determining the three-dimensional structure of proteins. Proteomics provides a starting point for researchers who would like a theoretical understanding of the new technologies in the field, and obtain a solid grasp of the fundamentals before integrating new tools into their experiments. Written with attention to detail, but without being overwhelmingly technical, Proteomics is a user-friendly guide needed by most biologists today.