Next generation sequencing is revolutionizing molecular biology. Owing to this new technology it is now possible to carry out a panoply of experiments at an unprecedented low cost and high speed. These go from sequencing whole genomes, transcriptomes and small non-coding RNAs to description of methylated regions, identification protein – DNA interaction sites and detection of structural variation. The generation of gigabases of sequence information for each of this huge bandwidth of applications in just a few days makes the development of bioinformatics applications for next generation sequencing data analysis as urgent as challenging.

Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.

Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.

The U.S. Department of Energy (DOE) promotes scientific and technological innovation to advance the national, economic, and energy security of the United States. Recognizing the potential of microorganisms to offer new energy alternatives and remediate environmental contamination, DOE initiated the Genomes to Life program, now called Genomics: GTL, in 2000. The program aims to develop a predictive understanding of microbial systems that can be used to engineer systems for bioenergy production and environmental remediation, and to understand carbon cycling and sequestration. This report provides an evaluation of the program and its infrastructure plan. Overall, the report finds that GTL's research has resulted in and promises to deliver many more scientific advancements that contribute to the achievement of DOE's goals. However, the DOE's current plan for building four independent facilities for protein production, molecular imaging, proteome analysis, and systems biology sequentially may not be the most cost-effective, efficient, and scientifically optimal way to provide this infrastructure. As an alternative, the report suggests constructing up to four institute-like facilities, each of which integrates the capabilities of all four of the originally planned facility types and focuses on one or two of DOE's mission goals. The alternative infrastructure plan could have an especially high ratio of scientific benefit to cost because the need for technology will be directly tied to the biology goals of the program.

Genomics in Aquaculture is a concise, must-have reference that describes current advances within the field of genomics and their applications to aquaculture. Written in an accessible manner for anyone—non-specialists to experts alike—this book provides in-depth coverage of genomics spanning from genome sequencing, to transcriptomics and proteomics. It provides, for ease of learning, examples from key species most relevant to current intensive aquaculture practice. Its coverage of minority species that have a specific biological interest (e.g., Pleuronectiformes) makes this book useful for countries that are developing such species. It is a robust, practical resource that covers foundational, functional, and applied aspects of genomics in aquaculture, presenting the most current information in a field of research that is rapidly growing. - Provides the latest scientific methods and technologies to maximize efficiencies for healthy fish production, with summary tables for quick reference - Offers an extended glossary of technical and methodological terms to help readers better understand key biological concepts - Describes state-of-the-art technologies, such as transcriptomics and epigenomics, currently under development for future perspective of the field - Covers minority species that have a specific biological interest (e.g., Pleuronectiformes), making the book useful to countries developing such species

Advances in Animal Genomics provides an outstanding collection of integrated strategies involving traditional and modern - omics (structural, functional, comparative and epigenomics) approaches and genomics-assisted breeding methods which animal biotechnologists can utilize to dissect and decode the molecular and gene regulatory networks involved in the complex quantitative yield and stress tolerance traits in livestock. Written by international experts on animal genomics, this book explores the recent advances in high-throughput, next-generation whole genome and transcriptome sequencing, array-based genotyping, and modern bioinformatics approaches which have enabled to produce huge genomic and transcriptomic resources globally on a genome-wide scale. This book is an important resource for researchers, students, educators and professionals in agriculture, veterinary and biotechnology sciences that enables them to solve problems regarding sustainable development with the help of current innovative biotechnologies. - Integrates basic and advanced concepts of animal biotechnology and presents future developments - Describes current high-throughput next-generation whole genome and transcriptome sequencing, array-based genotyping, and modern bioinformatics approaches for sustainable livestock production - Illustrates integrated strategies to dissect and decode the molecular and gene regulatory networks involved in complex quantitative yield and stress tolerance traits in livestock - Ensures readers will gain a strong grasp of biotechnology for sustainable livestock production with its well-illustrated discussion

The new field of toxicogenomics presents a potentially powerful set of tools to better understand the health effects of exposures to toxicants in the environment. At the request of the National Institute of Environmental Health Sciences, the National Research Council assembled a committee to identify the benefits of toxicogenomics, the challenges to achieving them, and potential approaches to overcoming such challenges. The report concludes that realizing the potential of toxicogenomics to improve public health decisions will require a concerted effort to generate data, make use of existing data, and study data in new waysâ€"an effort requiring funding, interagency coordination, and data management strategies.