This volume provides updates of this established field in both methods and applications, as well as advances in applications of the microarray method to biomarkers such as DNAs, RNAs, proteins, glycans and whole cells. Written for the Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Microarray Technology: Methods and Applications aims to ensure successful results in the further study of this vital field.

Protein microarrays soon will become one of the major tools for realizing the goals of drug discovery research in the post-genome era. The book is aimed at life science researchers and scientists working in drug and pharma industry.

Ithasbeenstatedthatourknowledgedoublesevery20years,butthatmaybe an understatement when considering the Life Sciences. A series of discoveries and inventions have propelled our knowledge from the recognition that DNA isthegeneticmaterialtoabasicmolecularunderstandingofourselvesandthe living world around us in less than 50 years. Crucial to this rapid progress was thediscoveryofthedouble-helicalstructureofDNA,whichlaidthefoundation forallhybridizationbasedtechnologies. Thediscoveriesofrestrictionenzymes, ligases, polymerases, combined with key innovations in DNA synthesis and sequencing ushered in the era of biotechnologyas a new science with profound sociological and economic implications that are likely to have a dominating in?uence on the development of our society during this century. Given the process by which science builds on prior knowledge, it is perhaps unfair to single out a few inventions and credit them with having contributed most to thisavalancheofknowledge. Yet,therearesurelysomethatwillberecognized as having had a more profound impact than others, not just in the furthering of our scienti?c knowledge, but by leveraging commercial applications that provide a tangible return to our society. The now famous Polymerase Chain Reaction, or PCR, is surely one of those, as it has uniquely catalyzed molecular biology during the past 20 years, and continues to have a signi?cant impact on all areas that involve nucleic acids, ranging from molecular pathology to forensics. Ten years ago micro- ray technology emerged as a new and powerful tool to study nucleic acid - quences in a highly multiplexed manner, and has since found equally exciting and useful applications in the study of proteins, metabolites, toxins, viruses, whole cells and even tissues.

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.

The effort to sequence the human genome has generated a new discipline, functional genomics, or the study of the relationship between the genetic code and its biologic potential. Gene expression studies are made possible not only by the decoding of the human genome, but by the development of new technologies. The preeminent technology in this area, DNA microarrays, is helping to revolutionize the field of neuroscience.

In recent years, high-density DNA microarrays have revolutionized biomedical research and drug discovery efforts by the pharmaceutical industry. Their efficacy in identifying and prioritizing drug targets based on their ability to confirm a large number of gene expression measurements in parallel has become a key element in drug discovery. Microarr

Technology standards for microarray research (M. Schena, R. W. Davis). Microfluidic technologies and instrumentation for printing DNA microarrays (Don Rose). Novel microarray printing and detection technologies (M. L. Mace Júnior, J. Montagu, Stanley D. Rose, G. McGuinness). A systems approach to fabricating and analyzing DNA microarrayss (J. Worley, K. Bechtol, S. Penn, D. Roach, D. hanzel, M. Trounstine, D. B.). The flow-thru chip: a three-dimensional biochip platform (A. Stell, M. Torres, J. Hartwell, Yong-Yi Yu, Nan Ting, G. Hoke, H. Yang). Large-scale genomic analysis using affymetrix genechip probe arrays (J. A. Warrington, S. Dee, M. Trulson). Technology and applications of gene expression microarrays (E. Evertsz, P. Starink, R. Gupta, D. Watson). Information processing issues and solutions associated with microarray technology (Y.-X. Zhou, P. Kalocsai, J.-Y. Chen, S. Shams). Microarray tools, kits, reagents, and services (T. Martinsky, P. Haje). Micromax: a highly sensitive system for differential gene expression on microarrays (K. Adler, J. Broadbent, R. Garlick, R. Joseph, A. Khimani, A. Mikulskis, P. Rapiejko, J. Killian). Production of microarrays on porous substrates using noncontact piezoelectric dispensing (D. Englert). Arrayed primer extension on the DNA chip: method and applications (N. Tonisson, A. Kurg, E. Lõhmussaar, A. Metspalu). Overview of a microarray scanner: design essentials for an integrated acquisition and analysis platform (T. Basarsky, D. Verdnik, J. Ye Zhai, D. Wellis). Selected supplier list. Index.

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.

Papers from CAMDA 2000, December 18-19, 2000, Duke University, Durham, NC, USA

This book is a comprehensive guide to all of the mathematics, statistics and computing you will need to successfully operate DNA microarray experiments. It is written for researchers, clinicians, laboratory heads and managers, from both biology and bioinformatics backgrounds, who work with, or who intend to work with microarrays. The book covers all aspects of microarray bioinformatics, giving you the tools to design arrays and experiments, to analyze your data, and to share your results with your organisation or with the international community. There are chapters covering sequence databases, oligonucleotide design, experimental design, image processing, normalisation, identifying differentially expressed genes, clustering, classification and data standards. The book is based on the highly successful Microarray Bioinformatics course at Oxford University, and therefore is ideally suited for teaching the subject at postgraduate or professional level.