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Two factors dominate current molecular biology: the amount of raw data is increasing very rapidly and successful applications in biomedical research require carefully curated and annotated databases. The quality of the experimental data -- especially nucleic acid sequences -- is satisfactory; however, annotations depend on features inferred from the data rather than measured directly, for instance the identification of genes in genome sequences. It is essential that these inferences are as accurate as possible and this requires human intervention. With the recognition of the importance of accurate database annotation and the requirement for individuals with particular constellations of skills to carry it out, annotators are emerging as specialists within the profession of bioinformatics. This book compiles information about annotation -- its current status, what is required to improve it, what skills must be brought to bear on database curation and hence what is the proper training for annotators. The book should be essential reading for all people working on biological databases, both biologists and computer scientists. It will also be of interest to all users of such databases, including molecular biologists, geneticists, protein chemists, clinicians and drug developers.
Two factors dominate current molecular biology: the amount of raw data is increasing very rapidly and successful applications in biomedical research require carefully curated and annotated databases. The quality of the experimental data -- especially nucleic acid sequences -- is satisfactory; however, annotations depend on features inferred from the data rather than measured directly, for instance the identification of genes in genome sequences. It is essential that these inferences are as accurate as possible and this requires human intervention. With the recognition of the importance of accurate database annotation and the requirement for individuals with particular constellations of skills to carry it out, annotators are emerging as specialists within the profession of bioinformatics. This book compiles information about annotation -- its current status, what is required to improve it, what skills must be brought to bear on database curation and hence what is the proper training for annotators. The book should be essential reading for all people working on biological databases, both biologists and computer scientists. It will also be of interest to all users of such databases, including molecular biologists, geneticists, protein chemists, clinicians and drug developers.
Sequence - Evolution - Function is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis. Sequence - Evolution - Function should help bridge the "digital divide" between biologists and computer scientists, allowing biologists to better grasp the peculiarities of the emerging field of Genome Biology and to learn how to benefit from the enormous amount of sequence data available in the public databases. The book is non-technical with respect to the computer methods for genome analysis and discusses these methods from the user's viewpoint, without addressing mathematical and algorithmic details. Prior practical familiarity with the basic methods for sequence analysis is a major advantage, but a reader without such experience will be able to use the book as an introduction to these methods. This book is perfect for introductory level courses in computational methods for comparative and functional genomics.
This book provides a practical and self-contained overview of the Gene Ontology (GO), the leading project to organize biological knowledge on genes and their products across genomic resources. Written for biologists and bioinformaticians, it covers the state-of-the-art of how GO annotations are made, how they are evaluated, and what sort of analyses can and cannot be done with the GO. In the spirit of the Methods in Molecular Biology book series, there is an emphasis throughout the chapters on providing practical guidance and troubleshooting advice. Authoritative and accessible, The Gene Ontology Handbook serves non-experts as well as seasoned GO users as a thorough guide to this powerful knowledge system. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.
The success of individualized medicine, advanced crops, and new and sustainable energy sources requires thoroughly annotated genomic information and the integration of this information into a coherent model. A thorough overview of this field, Genome Annotation explores automated genome analysis and annotation from its origins to the challenges of next-generation sequencing data analysis. The book initially takes you through the last 16 years since the sequencing of the first complete microbial genome. It explains how current analysis strategies were developed, including sequencing strategies, statistical models, and early annotation systems. The authors then present visualization techniques for displaying integrated results as well as state-of-the-art annotation tools, including MAGPIE, Ensembl, Bluejay, and Galaxy. They also discuss the pipelines for the analysis and annotation of complex, next-generation DNA sequencing data. Each chapter includes references and pointers to relevant tools. As very few existing genome annotation pipelines are capable of dealing with the staggering amount of DNA sequence information, new strategies must be developed to accommodate the needs of today’s genome researchers. Covering this topic in detail, Genome Annotation provides you with the foundation and tools to tackle this challenging and evolving area. Suitable for both students new to the field and professionals who deal with genomic information in their work, the book offers two genome annotation systems on an accompanying CD-ROM.
This book addresses the difficulties experienced by wet lab researchers with the statistical analysis of molecular biology related data. The authors explain how to use R and Bioconductor for the analysis of experimental data in the field of molecular biology. The content is based upon two university courses for bioinformatics and experimental biology students (Biological Data Analysis with R and High-throughput Data Analysis with R). The material is divided into chapters based upon the experimental methods used in the laboratories. Key features include: • Broad appeal--the authors target their material to researchers in several levels, ensuring that the basics are always covered. • First book to explain how to use R and Bioconductor for the analysis of several types of experimental data in the field of molecular biology. • Focuses on R and Bioconductor, which are widely used for data analysis. One great benefit of R and Bioconductor is that there is a vast user community and very active discussion in place, in addition to the practice of sharing codes. Further, R is the platform for implementing new analysis approaches, therefore novel methods are available early for R users.
This volume introduces software used for gene prediction with focus on eukaryotic genomes. The chapters in this book describe software and web server usage as applied in common use-cases, and explain ways to simplify re-annotation of long available genome assemblies. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary computational requirements, step-by-step, readily reproducible computational protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and thorough, Gene Prediction: Methods and Protocols is a valuable resource for researchers and research groups working on the assembly and annotation of single species or small groups of species. Chapter 3 is available open access under a CC BY 4.0 license via link.springer.com.
Life on Earth would be impossible without plants. Humans rely on plants for most clothing, furniture, food, as well as for many pharmaceuticals and other products. Plant genome sciences are essential to understanding how plants function and how to develop desirable plant characteristics. For example, plant genomic science can contribute to the development of plants that are drought-resistant, those that require less fertilizer, and those that are optimized for conversion to fuels such as ethanol and biodiesel. The National Plant Genome Initiative (NPGI) is a unique, cross-agency funding enterprise that has been funding and coordinating plant genome research successfully for nine years. Research breakthroughs from NPGI and the National Science Foundation (NSF) Arabidopsis 2010 Project, such as how the plant immune system controls pathogen defense, demonstrate that the plant genome science community is vibrant and capable of driving technological advancement. This book from the National Research Council concludes that these programs should continue so that applied programs on agriculture, bioenergy, and others will always be built on a strong foundation of fundamental plant biology research.
There is growing enthusiasm in the scientific community about the prospect of mapping and sequencing the human genome, a monumental project that will have far-reaching consequences for medicine, biology, technology, and other fields. But how will such an effort be organized and funded? How will we develop the new technologies that are needed? What new legal, social, and ethical questions will be raised? Mapping and Sequencing the Human Genome is a blueprint for this proposed project. The authors offer a highly readable explanation of the technical aspects of genetic mapping and sequencing, and they recommend specific interim and long-range research goals, organizational strategies, and funding levels. They also outline some of the legal and social questions that might arise and urge their early consideration by policymakers.
Bioinformatics for Beginners: Genes, Genomes, Molecular Evolution, Databases and Analytical Tools provides a coherent and friendly treatment of bioinformatics for any student or scientist within biology who has not routinely performed bioinformatic analysis. The book discusses the relevant principles needed to understand the theoretical underpinnings of bioinformatic analysis and demonstrates, with examples, targeted analysis using freely available web-based software and publicly available databases. Eschewing non-essential information, the work focuses on principles and hands-on analysis, also pointing to further study options. - Avoids non-essential coverage, yet fully describes the field for beginners - Explains the molecular basis of evolution to place bioinformatic analysis in biological context - Provides useful links to the vast resource of publicly available bioinformatic databases and analysis tools - Contains over 100 figures that aid in concept discovery and illustration