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DNA Methylation Microarrays Experimental Design and Statistical Analysis

DNA Methylation Microarrays Experimental Design and Statistical Analysis

Providing an interface between dry-bench bioinformaticians and wet-lab biologists DNA Methylation Microarrays: Experimental Design and Statistical Analysis presents the statistical methods and tools to analyze high-throughput epigenomic data in particular DNA methylation microarray data. Since these microarrays share the same underlying principles as gene expression microarrays many of the analyses in the text also apply to microarray-based gene expression and histone modification (ChIP-on-chip) studies. After introducing basic statistics the book describes wet-bench technologies that produce the data for analysis and explains how to preprocess the data to remove systematic artifacts resulting from measurement imperfections. It then explores differential methylation and genomic tiling arrays. Focusing on exploratory data analysis the next several chapters show how cluster and network analyses can link the functions and roles of unannotated DNA elements with known ones. The book concludes by surveying the open source software (R and Bioconductor) public databases and other online resources available for microarray research. Requiring only limited knowledge of statistics and programming this book helps readers gain a solid understanding of the methodological foundations of DNA microarray analysis. | DNA Methylation Microarrays Experimental Design and Statistical Analysis

GBP 59.99
1

Analyzing High-Dimensional Gene Expression and DNA Methylation Data with R

Analyzing High-Dimensional Gene Expression and DNA Methylation Data with R

Analyzing high-dimensional gene expression and DNA methylation data with R is the first practical book that shows a ``pipeline of analytical methods with concrete examples starting from raw gene expression and DNA methylation data at the genome scale. Methods on quality control data pre-processing data mining and further assessments are presented in the book and R programs based on simulated data and real data are included. Codes with example data are all reproducible. Features: · Provides a sequence of analytical tools for genome-scale gene expression data and DNA methylation data starting from quality control and pre-processing of raw genome-scale data. · Organized by a parallel presentation with explanation on statistical methods and corresponding R packages/functions in quality control pre-processing and data analyses (e. g. clustering and networks). · Includes source codes with simulated and real data to reproduce the results. Readers are expected to gain the ability to independently analyze genome-scaled expression and methylation data and detect potential biomarkers. This book is ideal for students majoring in statistics biostatistics and bioinformatics and researchers with an interest in high dimensional genetic and epigenetic studies.

GBP 66.99
1

Handbook of Forensic Statistics

Handbook of Forensic Statistics

Handbook of Forensic Statistics is a collection of chapters by leading authorities in forensic statistics. Written for statisticians scientists and legal professionals having a broad range of statistical expertise it summarizes and compares basic methods of statistical inference (frequentist likelihoodist and Bayesian) for trace and other evidence that links individuals to crimes the modern history and key controversies in the field and the psychological and legal aspects of such scientific evidence. Specific topics include uncertainty in measurements and conclusions; statistically valid statements of weight of evidence or source conclusions; admissibility and presentation of statistical findings; and the state of the art of methods (including problems and pitfalls) for collecting analyzing and interpreting data in such areas as forensic biology chemistry and pattern and impression evidence. The particular types of evidence that are discussed include DNA latent fingerprints firearms and toolmarks glass handwriting shoeprints and voice exemplars.

GBP 66.99
1

Introduction to Machine Learning and Bioinformatics

Introduction to Machine Learning and Bioinformatics

Lucidly Integrates Current Activities Focusing on both fundamentals and recent advances Introduction to Machine Learning and Bioinformatics presents an informative and accessible account of the ways in which these two increasingly intertwined areas relate to each other. Examines Connections between Machine Learning & Bioinformatics The book begins with a brief historical overview of the technological developments in biology. It then describes the main problems in bioinformatics and the fundamental concepts and algorithms of machine learning. After forming this foundation the authors explore how machine learning techniques apply to bioinformatics problems such as electron density map interpretation biclustering DNA sequence analysis and tumor classification. They also include exercises at the end of some chapters and offer supplementary materials on their website. Explores How Machine Learning Techniques Can Help Solve Bioinformatics Problems Shedding light on aspects of both machine learning and bioinformatics this text shows how the innovative tools and techniques of machine learning help extract knowledge from the deluge of information produced by today’s biological experiments.

GBP 59.99
1

Molecular and Cellular Biophysics

Molecular and Cellular Biophysics

From quantum theory to statistical mechanics the methodologies of physics are often used to explain some of life's most complex biological problems. Exploring this challenging yet fascinating area of study Molecular and Cellular Biophysics covers both molecular and cellular structures as well as the biophysical processes that occur in these structures. Designed for advanced undergraduate and beginning graduate students in biophysics courses this textbook features a quantitative approach that avoids being too abstract in its presentation. Logically organized from small-scale (molecular) to large-scale (cellular) systems the text first defines life discussing the scientific controversies between mechanists and vitalists the characteristics of living things and the evolution of life. It then delves into molecular structures including nucleic acids DNA RNA interatomic interactions and hydrogen bonds. After looking at these smaller systems the author probes the larger cellular structures. He examines the cytoplasm the cytoskeleton chromosomes mitochondria motor proteins and more. The book concludes with discussions on biophysical processes including oxidative phosphorylation diffusion bioenergetics conformational transitions in proteins vesicle transport subcellular structure formation and cell division.

GBP 59.99
1

Bioinformatics A Practical Approach

Bioinformatics A Practical Approach

An emerging ever-evolving branch of science bioinformatics has paved the way for the explosive growth in the distribution of biological information to a variety of biological databases including the National Center for Biotechnology Information. For growth to continue in this field biologists must obtain basic computer skills while computer specialists must possess a fundamental understanding of biological problems. Bridging the gap between biology and computer science Bioinformatics: A Practical Approach assimilates current bioinformatics knowledge and tools relevant to the omics age into one cohesive concise and self-contained volume. Written by expert contributors from around the world this practical book presents the most state-of-the-art bioinformatics applications. The first part focuses on genome analysis common DNA analysis tools phylogenetics analysis and SNP and haplotype analysis. After chapters on microarray SAGE regulation of gene expression miRNA and siRNA the book presents widely applied programs and tools in proteome analysis protein sequences protein functions and functional annotation of proteins in murine models. The last part introduces the programming languages used in biology website and database design and the interchange of data between Microsoft Excel and Access. Keeping complex mathematical deductions and jargon to a minimum this accessible book offers both the theoretical underpinnings and practical applications of bioinformatics. | Bioinformatics A Practical Approach

GBP 59.99
1

Introduction to Bioinformatics with R A Practical Guide for Biologists

Introduction to Bioinformatics with R A Practical Guide for Biologists

In biological research the amount of data available to researchers has increased so much over recent years it is becoming increasingly difficult to understand the current state of the art without some experience and understanding of data analytics and bioinformatics. An Introduction to Bioinformatics with R: A Practical Guide for Biologists leads the reader through the basics of computational analysis of data encountered in modern biological research. With no previous experience with statistics or programming required readers will develop the ability to plan suitable analyses of biological datasets and to use the R programming environment to perform these analyses. This is achieved through a series of case studies using R to answer research questions using molecular biology datasets. Broadly applicable statistical methods are explained including linear and rank-based correlation distance metrics and hierarchical clustering hypothesis testing using linear regression proportional hazards regression for survival data and principal component analysis. These methods are then applied as appropriate throughout the case studies illustrating how they can be used to answer research questions. Key Features: · Provides a practical course in computational data analysis suitable for students or researchers with no previous exposure to computer programming. · Describes in detail the theoretical basis for statistical analysis techniques used throughout the textbook from basic principles · Presents walk-throughs of data analysis tasks using R and example datasets. All R commands are presented and explained in order to enable the reader to carry out these tasks themselves. · Uses outputs from a large range of molecular biology platforms including DNA methylation and genotyping microarrays; RNA-seq genome sequencing ChIP-seq and bisulphite sequencing; and high-throughput phenotypic screens. · Gives worked-out examples geared towards problems encountered in cancer research which can also be applied across many areas of molecular biology and medical research. This book has been developed over years of training biological scientists and clinicians to analyse the large datasets available in their cancer research projects. It is appropriate for use as a textbook or as a practical book for biological scientists looking to gain bioinformatics skills. | Introduction to Bioinformatics with R A Practical Guide for Biologists

GBP 52.99
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