Download or read book A Pipeline for the Automatic Analysis of Microarray Data and Integrative Genomics for the Detection of Functional Modules written by Mattia Pelizzola and published by . This book was released on 2006 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Microarray Technology Through Applications written by Francesco Falciani and published by Garland Science. This book was released on 2007-06-11 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Microarray Technology Through Applications provides the reader with an understanding, from an applications perspective, of the diverse range of concepts required to master the experimental and data analysis aspects of microarray technology. The first chapter is a concise introduction to the technology and provides the theoretical background required to understand the subsequent sections. The following chapters are a series of case studies representative of the most general and important applications of microarray technology, including CGH, analysis of gene expression, SNP arrays and protein arrays. The case studies are written by experts in the field and describe prototypic projects, indicating how to generalize the approach to similar studies. There are detailed step-by-step protocols describing the specific experimental and data analysis protocols mentioned in the case study section. There is also information on printing glass DNA microarray slides and data interpretation. Colour figures and data sets are provided on the website at http://www.garlandscience.com/9780415378536
Download or read book Microarrays for an Integrative Genomics written by Isaac S. Kohane and published by Bradford Books. This book was released on 2003 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the use of DNA microarrays in functional genomics.
Download or read book Microarray Technology in Practice written by Steve Russell and published by Academic Press. This book was released on 2008-11-21 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using chips composed of thousands of spots, each with the capability of holding DNA molecules corresponding to a given gene, DNA microarray technology has enabled researchers to measure simultaneously gene expression across the genome. As with other large-scale genomics approaches, microarray technologies are broadly applicable across disciplines of life and biomedical sciences, but remain daunting to many researchers. This guide is designed to demystify the technology and inform more biologists about this critically important experimental technique. Cohesive overview of the technology and available platforms, followed by detailed discussion of experimental design and analysis of microarray experiments Up-to-date description of normalization methods and current methods for sample amplification and labeling Deep focus on oligonucleotide design, printing, labeling and hybridization, data acquisition, normalization, and meta-analysis Additional uses of microarray technology such as ChIP (chromatin immunoprecipitation) with hybridization to DNA arrays, microarray-based comparative genomic hybridization (CGH), and cell and tissue arrays
Download or read book Analysis of Microarray Data written by Matthias Dehmer and published by John Wiley & Sons. This book was released on 2008-09-08 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first to focus on the application of mathematical networks for analyzing microarray data. This method goes well beyond the standard clustering methods traditionally used. From the contents: * Understanding and Preprocessing Microarray Data * Clustering of Microarray Data * Reconstruction of the Yeast Cell Cycle by Partial Correlations of Higher Order * Bilayer Verification Algorithm * Probabilistic Boolean Networks as Models for Gene Regulation * Estimating Transcriptional Regulatory Networks by a Bayesian Network * Analysis of Therapeutic Compound Effects * Statistical Methods for Inference of Genetic Networks and Regulatory Modules * Identification of Genetic Networks by Structural Equations * Predicting Functional Modules Using Microarray and Protein Interaction Data * Integrating Results from Literature Mining and Microarray Experiments to Infer Gene Networks The book is for both, scientists using the technique as well as those developing new analysis techniques.
Download or read book A Practical Approach to Microarray Data Analysis written by Daniel P. Berrar and published by Springer Science & Business Media. This book was released on 2007-05-08 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Analysis of Microarray Gene Expression Data written by Mei-Ling Ting Lee and published by Springer Science & Business Media. This book was released on 2007-05-08 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Methods of Microarray Data Analysis written by Simon M. Lin and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 is one of the first books 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 focuses on two well-known data sets, 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.
Download or read book Microarray Innovations written by Gary Hardiman and published by CRC Press. This book was released on 2009-04-02 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Advanced Analysis Of Gene Expression Microarray Data written by Aidong Zhang and published by World Scientific Publishing Company. This book was released on 2006-06-27 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Methods of Microarray Data Analysis II written by Simon M. Lin and published by Springer Science & Business Media. This book was released on 2007-05-08 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book DNA Microarrays and Related Genomics Techniques written by David B. Allison and published by CRC Press. This book was released on 2005-11-14 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Microarrays for an Integrative Genomics written by Isaac S. Kohane and published by . This book was released on 2004 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Microarray Analysis written by Kal Sharma and published by Momentum Press. This book was released on 2015-06-15 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Microarray Analysis is a natural outgrowth of the author’s teaching and research into the fi eld of microarray processing, a fast growing and developing fi eld. There has been a reduction in the genominomics of sequencing of DNA and proteins: from $3 billion in HGP costs down to $1000 per genome in 2014 using next-generation sequencers. Different sequencing methods in place and various applications of these methods are illustrated. Commercially available Next-Generation Sequencers are compared side-side by side. This book will show how the biochemical reactions involved in the different steps of the cure process can be studied using microarray methods. Examples will be provided throughout the text of various disease states, including the spread of cystic fi brosis in children, consanguineous marriages in Saudi Arabia, genetic disorders, and autoimmune disorders. The protocols from sample preparation to confocal scanning microscopy and detectors using photo multiplier tubes to statistical data analysis methods will be discussed in detail. The Polymerase chain reaction, a technique used to amplify and simultaneously quantify a targeted DNA molecule is explored in relation to the best surface to be used for Microarray Analysis. Sanger sequencing, sequencing by synthesis, sequencing by ligation, single molecule sensing, DNA passage through nanopores in graphene are some methods used for obtaining sequence distribution information.
Download or read book Microarray Data Analysis written by Michael J. Korenberg and published by Humana. This book was released on 2014-10-31 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this new volume, renowned authors contribute fascinating, cutting-edge insights into microarray data analysis. Information on an array of topics is included in this innovative book including in-depth insights into presentations of genomic signal processing. Also detailed is the use of tiling arrays for large genomes analysis. The protocols follow the successful Methods in Molecular BiologyTM series format, offering step-by-step instructions, an introduction outlining the principles behind the technique, lists of the necessary equipment and reagents, and tips on troubleshooting and avoiding pitfalls.
Download or read book Automatic Pipeline for Microarray Image Analysis Based on Image Projections written by Mohamed Maoui and published by . This book was released on 2022 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Microarrays are a powerful tool for multiplexed analysis of DNA, RNA, proteins and EVs. They involve microarray designing, manufacturing, incubation with sample and fluorescent detection reagents, scanning, image processing, and data analyzing. Once the microarray images related to a particular experiment are produced, we follow a process of image analysis that is organized into three steps: gridding, segmentation, and intensity calculation. Ideally, the analysis would be much easier without noise sources that is mostly due to inhomogeneous spots intensities, dust, slides inhomogeneity and bias, as well as other challenges such as spots with noncircular shape or similar size, which require additional processing steps in order to accurately analyze the microarray data. Different software packages are available to analyze microarray data and overcome some of the traditional image analysis issues, such as ScanAlyze, and GenePix Pro6, or Array pro Analyzer. Unfortunately, these software require manual intervention to achieve accurate gridding, signal and background separation, as well as precise expression levels estimation, and they are "black boxes" which produce the final microarray image quantification results without showing most preprocessing or analysis steps such as channels splitting, or the denoising phase which is unsatisfactory and limits the ability to diagnose and correct image analysis errors. In this work, we developed an automated image analysis pipeline for microarray images, with emphasis on exosomes and EV analysis. The process of automation includes (1) gridding based on projection techniques (2) a thresholding image segmentation, and (3) an algorithm for intensity calculation. Different gridding parameters have been benchmarked based on the processing time, and accuracy of correctly gridding the spots, and its noise removal ability. We also explored the use of machine learning for microarray research by implementing k-means clustering algorithm on similar microarray images. We compared our data processing pipeline to Array Pro by using real microarray data from EV analysis experiments. Our automated pipeline, which is fast, effective with a gridding accuracy that gets to 97.5% and a segmentation similarity of 98%, can improve our understanding of the image analysis steps of many software used to analyze microarray data, and offer a universal way for more accurate analysis of microarray data and EVs, by assessing different quality metrics of any type of microarray, and therefore help in answering different biological questions"--
Download or read book Microarray Analysis of the Physical Genome written by Jonathan R. Pollack and published by Humana Press. This book was released on 2011-12-06 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the early years of microarray technology, efforts were directed mainly at profiling expressed genes, while recently the microarray platform has been adapted into diverse applications directed toward the investigation of the physical genome. In Microarray Analysis of the Physical Genome: Methods and Protocols, experts in the field cover DNA microarray applications for the detection and characterization of genomic DNA-associated copy number alteration, loss of heterozygosity (LOH), cytosine methylation, protein binding sites, regulatory elements, and replication timing, with an emphasis on higher eukaryote (animal) and cancer genomes. Written in the highly successful Methods in Molecular BiologyTM series format, chapters include a brief introduction to their respective subjects, lists of the necessary materials and reagents, step-by-step protocols, and time-saving notes on troubleshooting and avoiding known pitfalls. Authoritative and easy-to-use, Microarray Analysis of the Physical Genome: Methods and Protocols is of great value to the molecular biologist or computational biologist interested in understanding the principles of these analyses or in planning future experiments using microarrays to characterize the physical genome.
