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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.
Enzymes, lignin, proteins, cellulose, pectin, kinase.
The prediction of the conformation of proteins has developed from an intellectual exercise into a serious practical endeavor that has great promise to yield new stable enzymes, products of pharmacological significance, and catalysts of great potential. With the application of predic tion gaining momentum in various fields, such as enzymology and immunology, it was deemed time that a volume be published to make available a thorough evaluation of present methods, for researchers in this field to expound fully the virtues of various algorithms, to open the field to a wider audience, and to offer the scientific public an opportunity to examine carefully its successes and failures. In this manner the practitioners of the art could better evaluate the tools and the output so that their expectations and applications could be more realistic. The editor has assembled chapters by many of the main contributors to this area and simultaneously placed their programs at three national resources so that they are readily available to those who wish to apply them to their personal interests. These algorithms, written by their originators, when utilized on pes or larger computers, can instantaneously take a primary amino acid sequence and produce a two-or three-dimensional artistic image that gives satisfaction to one's esthetic sensibilities and food for thought concerning the structure and function of proteins. It is in this spirit that this volume was envisaged.
Based on ideas from Support Vector Machines (SVMs), Learning To Classify Text Using Support Vector Machines presents a new approach to generating text classifiers from examples. The approach combines high performance and efficiency with theoretical understanding and improved robustness. In particular, it is highly effective without greedy heuristic components. The SVM approach is computationally efficient in training and classification, and it comes with a learning theory that can guide real-world applications. Learning To Classify Text Using Support Vector Machines gives a complete and detailed description of the SVM approach to learning text classifiers, including training algorithms, transductive text classification, efficient performance estimation, and a statistical learning model of text classification. In addition, it includes an overview of the field of text classification, making it self-contained even for newcomers to the field. This book gives a concise introduction to SVMs for pattern recognition, and it includes a detailed description of how to formulate text-classification tasks for machine learning.
The LNCS journal Transactions on Computational Systems Biology is devoted to inter- and multidisciplinary research in the fields of computer science and life sciences and supports a paradigmatic shift in the techniques from computer and information science to cope with the new challenges arising from the systems oriented point of view of biological phenomena. This second volume of the Transactions on Computational Systems Biology is devoted to considerably extended versions of selected papers presented at the International Workshop on Bioinformatics Research and Applications (IWBRA 2005), part of the International Conference on Computational Science (ICCS 2005), which took place at Emory University, Atlanta, Georgia, USA, in May 2005. The ten papers selected for the special issue cover a wide range of bioinformatics research such as problems in RNA structure prediction, coding schemes and structural alphabets for protein structure prediction, novel techniques for efficient gene transfer in phylogenetic networks, practical algorithms minimizing recombinations in pedigree phasing, parallel implementation in Open MP for finding the corresponding shortest edit distance between two signed gene permutations, and bioinformatics problems in DNA microarrays.
This thorough book collects methods and strategies to analyze proteomics data. It is intended to describe how data obtained by gel-based or gel-free proteomics approaches can be inspected, organized, and interpreted to extrapolate biological information. Organized into four sections, the volume explores strategies to analyze proteomics data obtained by gel-based approaches, different data analysis approaches for gel-free proteomics experiments, bioinformatic tools for the interpretation of proteomics data to obtain biological significant information, as well as methods to integrate proteomics data with other omics datasets including genomics, transcriptomics, metabolomics, and other types of data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that will ensure high quality results in the lab. Authoritative and practical, Proteomics Data Analysis serves as an ideal guide to introduce researchers, both experienced and novice, to new tools and approaches for data analysis to encourage the further study of proteomics.
Computer scientists have increasingly been enlisted as "bioinformaticians" to assist molecular biologists in their research. This book is a practical introduction to bioinformatics for these computer scientists. The chapters are in-depth discussions by expert bioinformaticians on both general techniques and specific approaches to a range of selected bioinformatics problems. The book is organized into clusters of chapters on the following topics: - Overview of modern molecular biology and a broad spectrum of techniques from computer science -- data mining, machine learning, mathematical modeling, sequence alignment, data integration, workflow development, etc. - In-depth discussion of computational recognition of functional and regulatory sites in DNA sequences. - Incisive discussion of computational prediction of secondary structure of RNA sequences. - Overview of computational prediction of protein cellular localization, and selected discussions of inference of protein function. - Overview of methods for discovering protein-protein interactions. - Detailed discussion of approaches to gene expression analysis for the diagnosis of diseases, the treatment of diseases, and the understanding of gene functions. - Case studies on analysis of phylogenies, functional annotation of proteins, construction of purposebuilt integrated biological databases, and development of workflows underlying the large-scale-effort gene discovery. - Written in a practical, in-depth tutorial style - Covers a broad range of bioinformatics topics and of techniques used in bioinformatics - Comprehensive overviews of the development of various approaches in a number of selectedtopics - In-depth exposition of a number of important topics - Contributions by prominent researchers: Vladimir Bajic, Ming Li, Kenta Nakai, Limsoon Wong, Cathy Wu, etc. - Extensive, integrated references to background liter
Protein transport into and across membranes is a fundamental process in bacteria that touches upon and unites many areas of microbiology, including bacterial cell physiology, adhesion and motility, nutrient scavenging, intrabacterial signaling and social behavior, toxin deployment, interbacterial antagonism and collaboration, host invasion and disruption, and immune evasion. A broad repertoire of mechanisms and macromolecular machines are required to deliver protein substrates across bacterial cell membranes for intended effects. Some machines are common to most, if not all bacteria, whereas others are specific to Gram-negative or Gram-positive species or species with unique cell envelope properties such as members of Actinobacteria and Spirochetes. Protein Secretion in Bacteria, authored and edited by an international team of experts, draws together the many distinct functions and mechanisms involved in protein translocation in one concise tome. This comprehensive book presents updated information on all aspects of bacterial protein secretion encompassing: Individual secretory systems–Sec, Tat, and T1SS through the newly discovered T9SS Mechanisms, structures, and functions of bacterial secretion systems Lipoprotein sorting pathways, outer membrane vesicles, and the sortase system Structures and roles of surface organelles, including flagella, pili, and curli Emerging technologies and translational implications Protein Secretion in Bacteria serves as both an introductory guide for students and postdocs and a ready reference for seasoned researchers whose work touches on protein export and secretion. This volume synthesizes the diversity of mechanisms of bacterial secretion across the microbial world into a digestible resource to stimulate new research, inspire continued identification and characterization of novel systems, and bring about new ways to manipulate these systems for biotechnological, preventative, and therapeutic applications.
Heat shock proteins are emerging as important molecules in the development of cancer and as key targets in cancer therapy. These proteins enhance the growth of cancer cells and protect tumors from treatments such as drugs or surgery. However, new drugs have recently been developed particularly those targeting heat shock protein 90. As heat shock protein 90 functions to stabilize many of the oncogenes and growth promoting proteins in cancer cells, such drugs have broad specificity in many types of cancer cell and offer the possibility of evading the development of resistance through point mutation or use of compensatory pathways. Heat shock proteins have a further property that makes them tempting targets in cancer immunotherapy. These proteins have the ability to induce an inflammatory response when released in tumors and to carry tumor antigens to antigen presenting cells. They have thus become important components of anticancer vaccines. Overall, heat shock proteins are important new targets in molecular cancer therapy and can be approached in a number of contrasting approaches to therapy.