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.

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.

The book aims to introduce the reader to the emerging field of Evolutionary Systems Biology, which approaches classical systems biology questions within an evolutionary framework. An evolutionary approach might allow understanding the significance of observed diversity, uncover “evolutionary design principles” and extend predictions made in model organisms to others. In addition, evolutionary systems biology can generate new insights into the adaptive landscape by combining molecular systems biology models and evolutionary simulations. This insight can enable the development of more detailed mechanistic evolutionary hypotheses.

"All the King's horses and all the King's mm couldn't put Humpty Dumpty together again." It is entirely possible that the difficulty facing "all the King's men" was principally the lack of a sufficient guide to the techniques of reassembling from a series of small components, the original entity. It is the sincere hope of the editor of the present work and of each of the contributing authors that the modern researcher will not face a similar predicament in his endeavours to reconstruct the complete primary sequence of a protein from the array of component amino acids. Rather, it is the intent that, with this volume, he may proceed untimorously if not with outright confidence toward achieving his purpose. To the newcomer in protein sequencing, compelled by necessity, or fascination, to investigate the exact order of amino acids in proteins, the question of "where to begin" - or "how to do it" is urgent. To those more skilled, a ready source of additional techniques should nevertheless be of value. This volume attempts to present in a single source a discussion of the methods and techniques useful to the determination of the primary structures of proteins and peptides. Hopefully, this book will tell the reader "how to do it".

The recent accumulation of information from genomes, including their sequences, has resultednotonlyinnewattemptstoansweroldquestionsandsolvelongstandingissues inbiology,butalsointheformulationofnovelhypothesesthatarisepreciselyfromthis wealth of data. The storage, processing, description, transmission, connection, and analysis of these data has prompted bioinformatics to become one the most relevant applied sciences for this new century, walking hand-in-hand with modern molecular biology and clearly impacting areas like biotechnology and biomedicine. Bioinformatics skills have now become essential for many scientists working with DNA sequences. With this idea in mind, this book aims to provide practical guidance andtroubleshootingadviceforthecomputationalanalysisofDNAsequences,covering a range of issues and methods that unveil the multitude of applications and relevance that Bioinformatics has today. The analysis of protein sequences has been purposely excludedtogainfocus.Individualbookchaptersareorientedtowardthedescriptionof theuseofspecificbioinformaticstools,accompaniedbypracticalexamples,adiscussion on the interpretation of results, and specific comments on strengths and limitations of the methods and tools. In a sense, chapters could be seen as enriched task-oriented manuals that will direct the reader in completing specific bioinformatics analyses. The target audience for this book is biochemists, and molecular and evolutionary biologiststhatwanttolearnhowtoanalyzeDNAsequencesinasimplebutmeaningful fashion. Readers do not need a special background in statistics, mathematics, or computer science, just a basic knowledge of molecular biology and genetics. All the tools described in the book are free and all of them can be downloaded or accessed throughtheweb.Mostchapterscouldbeusedforpracticaladvancedundergraduateor graduate-level courses in bioinformatics and molecular evolution.