Dna Microarrays And Gene Expression

Massive data acquisition technologies, such as genome sequencing, high-throughput drug screening, and DNA arrays are in the process of revolutionizing biology and medicine. Using the mRNA of a given cell, at a given time, under a given set of conditions, DNA microarrays can provide a snapshot of the level of expression of all the genes in the cell. Such snapshots can be used to study fundamental biological phenomena such as development or evolution, to determine the function of new genes, to infer the role individual genes or groups of genes may play in diseases, and to monitor the effect of drugs and other compounds on gene expression. Originally published in 2002, this inter-disciplinary introduction to DNA arrays will be of value to anyone with an a interest in this powerful technology.

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.

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

DNA Microarrays: Methods Express covers the very latest in DNA microarray technology, with a clear focus on how these techniques can be used in the lab to gain the very best results. The authors are from some of the leading laboratories in the field and write with real authority on the latest methodology. Every chapter provides detailed step-by-step protocols with valuable hints and tips for success, as well as giving typical experimental results and selected literature citations. This book is a 'must have' manual for researchers in all fields of biology, medicine and agriculture.

DNA Microarrays introduces all up-to-date microarray platforms and their various applications. It is written for scientists who are entering the field of DNA microarrays as well as those already familiar with the technology, but interested in new applications and methods.

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

This guide covers aspects of designing microarray experiments and analysing the data generated, including information on some of the tools that are available from non-commercial sources. Concepts and principles underpinning gene expression analysis are emphasised and wherever possible, the mathematics has been simplified. The guide is intended for use by graduates and researchers in bioinformatics and the life sciences and is also suitable for statisticians who are interested in the approaches currently used to study gene expression. Microarrays are an automated way of carrying out thousands of experiments at once, and allows scientists to obtain huge amounts of information very quickly Short, concise text on this difficult topic area Clear illustrations throughout Written by well-known teachers in the subject Provides insight into how to analyse the data produced from microarrays

This book focuses on the development and application of the latest advanced data mining, machine learning, and visualization techniques for the identification of interesting, significant, and novel patterns in gene expression microarray data.Biomedical researchers will find this book invaluable for learning the cutting-edge methods for analyzing gene expression microarray data. Specifically, the coverage includes the following state-of-the-art methods:• Gene-based analysis: the latest novel clustering algorithms to identify co-expressed genes and coherent patterns in gene expression microarray data sets• Sample-based analysis: supervised and unsupervised methods for the reduction of the gene dimensionality to select significant genes. A series of approaches to disease classification and discovery are also described• Pattern-based analysis: methods for ascertaining the relationship between (subsets of) genes and (subsets of) samples. Various novel pattern-based clustering algorithms to find the coherent patterns embedded in the sub-attribute spaces are discussed• Visualization tools: various methods for gene expression data visualization. The visualization process is intended to transform the gene expression data set from high-dimensional space into a more easily understood two- or three-dimensional space.