Patterns In Protein Sequence And Structure

The contents of this volume derive loosely from an EMBO worksh9P held at EMBL (Heidelberg) towards the end of 1989. The topic of Patterns in Protein Sequence and Structure attracted a wide range of participants, from biochemists to computer scientists, and that diversity has, to some extent, remained in the contributions to this volume. The problems of interpreting biological sequence data are to an increasing extent forcing molecular biologists to learn the language of computers, including at times, even the abstruse language of the computer scientists themselves. While, on their side, the computer scientists have discovered a veritable honey-pot of real data on which to test their algorithms. This enforced meeting of two otherwise alien fields has resulted in some difficulties in communication and it was an aim of the EMBO workshop to help resolve these. By the end, most biologists at the meeting had, at least, heard the terms Dynamic Programming and Regular Expression while for their part the computer programmers began to realise that protein sequences might be more than simple Markov chains in a 20-letter alphabet. Thanks to the modern facilities at EMBL, the three day meeting was video-taped and from this a transcript was taken and offered to the speakers as the basis for a contribution to this volume.

The contents of this volume derive loosely from an EMBO worksh9P held at EMBL (Heidelberg) towards the end of 1989. The topic of Patterns in Protein Sequence and Structure attracted a wide range of participants, from biochemists to computer scientists, and that diversity has, to some extent, remained in the contributions to this volume. The problems of interpreting biological sequence data are to an increasing extent forcing molecular biologists to learn the language of computers, including at times, even the abstruse language of the computer scientists themselves. While, on their side, the computer scientists have discovered a veritable honey-pot of real data on which to test their algorithms. This enforced meeting of two otherwise alien fields has resulted in some difficulties in communication and it was an aim of the EMBO workshop to help resolve these. By the end, most biologists at the meeting had, at least, heard the terms Dynamic Programming and Regular Expression while for their part the computer programmers began to realise that protein sequences might be more than simple Markov chains in a 20-letter alphabet. Thanks to the modern facilities at EMBL, the three day meeting was video-taped and from this a transcript was taken and offered to the speakers as the basis for a contribution to this volume.

This book explores the remarkable information correspondences and probability structures of proteins. Correspondences are pervasive in biochemistry and bioinformatics: proteins share homologies, folding patterns, and mechanisms. Probability structures are just as paramount: folded state graphics reflect Angstrom-scale maps of electron density. The author explores protein sequences (primary structures), both individually and in sets (systems) with the help of probability and information tools. This perspective will enhance the reader’s knowledge of how an important class of molecules is designed and put to task in natural systems, and how we can approach class members in hands-on ways.

Essential Bioinformatics is a concise yet comprehensive textbook of bioinformatics, which provides a broad introduction to the entire field. Written specifically for a life science audience, the basics of bioinformatics are explained, followed by discussions of the state-of-the-art computational tools available to solve biological research problems. All key areas of bioinformatics are covered including biological databases, sequence alignment, genes and promoter prediction, molecular phylogenetics, structural bioinformatics, genomics and proteomics. The book emphasizes how computational methods work and compares the strengths and weaknesses of different methods. This balanced yet easily accessible text will be invaluable to students who do not have sophisticated computational backgrounds. Technical details of computational algorithms are explained with a minimum use of mathematical formulae; graphical illustrations are used in their place to aid understanding. The effective synthesis of existing literature as well as in-depth and up-to-date coverage of all key topics in bioinformatics make this an ideal textbook for all bioinformatics courses taken by life science students and for researchers wishing to develop their knowledge of bioinformatics to facilitate their own research.

Finding patterns in biomolecular data, particularly in DNA and RNA, is at the center of modern biological research. These data are complex and growing rapidly, so the search for patterns requires increasingly sophisticated computer methods. Pattern Discovery in Biomolecular Data provides a clear, up-to-date summary of the principal techniques. Each chapter is self-contained, and the techniques are drawn from many fields, including graph theory, information theory, statistics, genetic algorithms, computer visualization, and vision. Since pattern searches often benefit from multiple approaches, the book presents methods in their purest form so that readers can best choose the method or combination that fits their needs. The chapters focus on finding patterns in DNA, RNA, and protein sequences, finding patterns in 2D and 3D structures, and choosing system components. This volume will be invaluable for all workers in genomics and genetic analysis, and others whose research requires biocomputing.

The three-dimensional structure of proteins is a key factor in their biological activity. There is an increasing need to be able to predict the structure of a protein once its amino-acid sequence is known; this book presents practical methods of achieving that ambitious aim, using the latest computer modelling algorithms. - ;The prediction of the three-dimensional structure of a protein from its sequence is a problem faced by an ever-increasing number of biological scientists as they strive to utilize genetic information. The increasing sizes of the sequence and structural databases, the improvements in computing power, and the deeper understanding of the principles of protein structure have led to major developments in the field in the last few years. This book presents practical computer-based methods using the latest computer modelling algorithms. -

Pairwise global alignment of sequences. Pairwise local alignment and database search. Statical analysis. Multiple global alignment and phylogenetic trees. Scoring matrices. Profiles. Sequence patterns. Structures and structure descriptions. Superposition and Dynamic programming. Geometric techniques. Clustering: Combining local similarities. Significance and assessment of structure comparisons. Multiple structure comparison. Protein structure classification. Structure prediction: Threading. Basics in mathematics, probability and algorithms. Introduction to molecular biology.