Overview and Goals This book describes how to visualize and compare bacterial genomes. Sequencing technologies are becoming so inexpensive that soon going for a cup of coffee will be more expensive than sequencing a bacterial genome. Thus, there is a very real and pressing need for high-throughput computational methods to compare hundreds and thousands of bacterial genomes. It is a long road from molecular biology to systems biology, and in a sense this text can be thought of as a path bridging these ? elds. The goal of this book is to p- vide a coherent set of tools and a methodological framework for starting with raw DNA sequences and producing fully annotated genome sequences, and then using these to build up and test models about groups of interacting organisms within an environment or ecological niche. Organization and Features The text is divided into four main parts: Introduction, Comparative Genomics, Transcriptomics and Proteomics, and ? nally Microbial Communities. The ? rst ? ve chapters are introductions of various sorts. Each of these chapters represents an introduction to a speci? c scienti? c ? eld, to bring all readers up to the same basic level before proceeding on to the methods of comparing genomes. First, a brief overview of molecular biology and of the concept of sequences as biological inf- mation are given.

This textbook is for anyone who needs to learn the basics of bioinformatics—the use of computational methods to better understand biological systems. Computational Biology covers the principles and applications of the computational methods used to study DNA, RNA, and proteins, including using biological databases such as NCBI and UniProt; performing BLAST, sequence alignments, and structural predictions; and creating phylogenetic trees. It includes a primer that can be used as a jumping off point for learning computer programming for bioinformatics. This text can be used as a self-study guide, as a course focused on computational methods in biology/bioinformatics, or to supplement general courses that touch on topics included within the book. Computational Biology's robust interactive online components “gamify” the study of bioinformatics, allowing the reader to practice randomly generated problems on their own time to build confidence and skill and gain practical real-world experience. The online component also assures that the content being taught is up to date and accurately reflects the ever-changing landscape of bioinformatics web-based programs.

The Chemical Sciences Roundtable provides a forum for discussing chemically related issues affecting government, industry and government. The goal is to strengthen the chemical sciences by foster communication among all the important stakeholders. At a recent Roundtable meeting, information technology was identified as an issue of increasing importance to all sectors of the chemical enterprise. This book is the result of a workshop convened to explore this topic.

Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.

Computational Genomics and Structural Bioinformatics in Microbial Science: Microbial Genomics (Volume 2) covers different aspects of microbial genomics, metagenomics, and functional studies of microbes through informative illustrations of current trends in computational tools and bioinformatics approach in environmental microbiology and clinical diagnosis. This book aims to provide readers with an overview of the microbial genome, computational genomics, and structural bioinformatics in microbial science, as well as the most recent developments in these fields. This book covers a range of topics, including the challenges and opportunities of computational epigenomics, bioinformatics tools for assessing metagenomic data, as well as computed comparative genomics and computational phenotyping of microorganisms relevant to agriculture. Microbial Genomics: Host Adaptation, virulence, and Evolution is a valuable resource for faculty members, researchers, and undergraduate and postgraduate students at universities, medical research labs, that are interested in microbial science specifically related to the microbial genome, computing genomics, and bioinformatics. - Provides informative illustrations of current trends in computational tools and bioinformatics approach - Presents bioinformatics of next generation sequencing in clinical microbiology diagnosis - Discusses structural bioinformatics and its applications

Where did SARS come from? Have we inherited genes from Neanderthals? How do plants use their internal clock? The genomic revolution in biology enables us to answer such questions. But the revolution would have been impossible without the support of powerful computational and statistical methods that enable us to exploit genomic data. Many universities are introducing courses to train the next generation of bioinformaticians: biologists fluent in mathematics and computer science, and data analysts familiar with biology. This readable and entertaining book, based on successful taught courses, provides a roadmap to navigate entry to this field. It guides the reader through key achievements of bioinformatics, using a hands-on approach. Statistical sequence analysis, sequence alignment, hidden Markov models, gene and motif finding and more, are introduced in a rigorous yet accessible way. A companion website provides the reader with Matlab-related software tools for reproducing the steps demonstrated in the book.