The existence of genes for RNA molecules not coding for proteins (ncRNAs) has been recognized since the 1950's, but until recently, aside from the critically important ribosomal and transfer RNA genes, most focus has been on protein coding genes. However, a long series of striking discoveries, from RNA's ability to carry out catalytic function, to discovery of riboswitches, microRNAs and other ribo-regulators performing critical tasks in essentially all living organisms, has created a burgeoning interest in this primordial component of the biosphere. However, the structural characteristics and evolutionary constraints on RNA molecules are very different from those of proteins, necessitating development of a completely new suite of informatic tools to address these challenges. In RNA Sequence, Structure, Function: Computational and Bioinformatic Methods, expert researchers in the field describe a substantial and relevant fraction of these methodologies from both practical and computational/algorithmic perspectives. Focusing on both of these directions addresses both the biologist interested in knowing more about RNA bioinformatics as well as the bioinformaticist interested in more detailed aspects of the algorithms. Written in the highly successful Methods in Molecular Biology series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results. Thorough and intuitive, RNA Sequence, Structure, Function: Computational and Bioinformatic Methods aids scientists in continuing to study key methods and principles of RNA bioinformatics.

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.

Bioinformatics: Methods and Applications provides a thorough and detailed description of principles, methods, and applications of bioinformatics in different areas of life sciences. It presents a compendium of many important topics of current advanced research and basic principles/approaches easily applicable to diverse research settings. The content encompasses topics such as biological databases, sequence analysis, genome assembly, RNA sequence data analysis, drug design, and structural and functional analysis of proteins. In addition, it discusses computational approaches for vaccine design, systems biology and big data analysis, and machine learning in bioinformatics.It is a valuable source for bioinformaticians, computer biologists, and members of biomedical field who needs to learn bioinformatics approaches to apply to their research and lab activities. - Covers basic and more advanced developments of bioinformatics with a diverse and interdisciplinary approach to fulfill the needs of readers from different backgrounds - Explains in a practical way how to decode complex biological problems using computational approaches and resources - Brings case studies, real-world examples and several protocols to guide the readers with a problem-solving approach

With the dramatic increase in RNA 3D structure determination in recent years, we now know that RNA molecules are highly structured. Moreover, knowledge of RNA 3D structures has proven crucial for understanding in atomic detail how they carry out their biological functions. Because of the huge number of potentially important RNA molecules in biology, many more than can be studied experimentally, we need theoretical approaches for predicting 3D structures on the basis of sequences alone. This volume provides a comprehensive overview of current progress in the field by leading practitioners employing a variety of methods to model RNA 3D structures by homology, by fragment assembly, and by de novo energy and knowledge-based approaches.

Bridges the gap between bioinformaticists and molecular biologists, i.e. the developers and the users of computational methods for biological data analysis and in that it presents examples of practical applications of the bioinformatics tools in the "daily practice" of an experimental research scientist.

Bioinformatics and Computational Biology: Technological Advancements, Applications and Opportunities is an invaluable resource for general and applied researchers who analyze biological data that is generated, at an unprecedented rate, at the global level. After careful evaluation of the requirements for current trends in bioinformatics and computational biology, it is anticipated that the book will provide an insightful resource to the academic and scientific community. Through a myriad of computational resources, algorithms, and methods, it equips readers with the confidence to both analyze biological data and estimate predictions. The book offers comprehensive coverage of the most essential and emerging topics: Cloud-based monitoring of bioinformatics multivariate data with cloud platforms Machine learning and deep learning in bioinformatics Quantum machine learning for biological applications Integrating machine learning strategies with multiomics to augment prognosis in chronic diseases Biomedical engineering Next generation sequencing techniques and applications Computational systems biology and molecular evolution While other books may touch on some of the same issues and nuances of biological data analysis, they neglect to feature bioinformatics and computational biology exclusively, and as exhaustively. This book's abundance of several subtopics related to almost all of the regulatory activities of biomolecules from where real data is being generated brings an added dimension.

Bioinformatics for Everyone provides a brief overview on currently used technologies in the field of bioinformatics—interpreted as the application of information science to biology— including various online and offline bioinformatics tools and softwares. The book presents valuable knowledge in a simplified way to help students and researchers easily apply bioinformatics tools and approaches to their research and lab routines. Several protocols and case studies that can be reproduced by readers to suit their needs are also included. - Explains the most relevant bioinformatics tools available in a didactic manner so that readers can easily apply them to their research - Includes several protocols that can be used in different types of research work or in lab routines - Discusses upcoming technologies and their impact on biological/biomedical sciences

The structural biology of protein-nucleic acid interactions is in some ways a mature field and in others in its infancy. High-resolution structures of protein-DNA complexes have been studied since the mid 1980s and a vast array of such structures has now been determined, but surprising and novel structures still appear quite frequently. High-resolution structures of protein-RNA complexes were relatively rare until the last decade. Propelled by advances in technology as well as the realization of RNA's importance to biology, the number of example structures has ballooned in recent years. New insights are now being gained from comparative studies only recently made possible due to the size of the database, as well as from careful biochemical and biophysical studies. As a result of the explosion of research in this area, it is no longer possible to write a comprehensive review. Instead, current review articles tend to focus on particular subtopics of interest. This makes it difficult for newcomers to the field to attain a solid understanding of the basics. One goal of this book is therefore to provide in-depth discussions of the fundamental principles of protein-nucleic acid interactions as well as to illustrate those fundamentals with up-to-date and fascinating examples for those who already possess some familiarity with the field. The book also aims to bridge the gap between the DNA- and the RNA- views of nucleic acid - protein recognition, which are often treated as separate fields. However, this is a false dichotomy because protein - DNA and protein - RNA interactions share many general principles. This book therefore includes relevant examples from both sides, and frames discussions of the fundamentals in terms that are relevant to both. The monograph approaches the study of protein-nucleic acid interactions in two distinctive ways. First, DNA-protein and RNA-protein interactions are presented together. Second, the first half of the book develops the principles of protein-nucleic acid recognition, whereas the second half applies these to more specialized topics. Both halves are illustrated with important real life examples. The first half of the book develops fundamental principles necessary to understand function. An introductory chapter by the editors reviews the basics of nucleic acid structure. Jen-Jacobsen and Jacobsen discuss how solvent interactions play an important role in recognition, illustrated with extensive thermodynamic data on restriction enzymes. Marmorstein and Hong introduce the zoology of the DNA binding domains found in transcription factors, and describe the combinational recognition strategies used by many multiprotein eukaryotic complexes. Two chapters discuss indirect readout of DNA sequence in detail: Berman and Lawson explain the basic principles and illustrate them with in-depth studies of CAP, while in their chapter on DNA bending and compaction Johnson, Stella and Heiss highlight the intrinsic connections between DNA bending and indirect readout. Horvath lays out the fundamentals of protein recognition of single stranded DNA and single stranded RNA, and describes how they apply in a detailed analysis of telomere end binding proteins. Nucleic acids adopt more complex structures - Lilley describes the conformational properties of helical junctions, and how proteins recognize and cleave them. Because RNA readily folds due to the stabilizing role of its 2'-hydroxyl groups, Li discusses how proteins recognize different RNA folds, which include duplex RNA. With the fundamentals laid out, discussion turns to more specialized examples taken from important aspects of nucleic acid metabolism. Schroeder discusses how proteins chaperone RNA by rearranging its structure into a functional form. Berger and Dong discuss how topoisomerases alter the topology of DNA and relieve the superhelical tension introduced by other processes such as replication and transcription. Dyda and Hickman show how DNA transposes mediate genetic mobility and Van Duyne discusses how site-specific recombinases "cut" and "paste" DNA. Horton presents a comprehensive review of the structural families and chemical mechanisms of DNA nucleases, whereas Li in her discussion of RNA-protein recognition also covers RNA nucleases. Lastly, FerrÚ-D'AmarÚ shows how proteins recognize and modify RNA transcripts at specific sites. The book also emphasises the impact of structural biology on understanding how proteins interact with nucleic acids and it is intended for advanced students and established scientists wishing to broaden their horizons.

This book explores recent progress in RNA secondary, tertiary structure prediction, and its application from an expansive point of view. Because of advancements in experimental protocols and devices, the integration of new types of data as well as new analysis techniques is necessary, and this volume discusses additional topics that are closely related to RNA structure prediction, such as the detection of structure-disrupting mutations, high-throughput structure analysis, and 3D structure design. Written for the highly successful Methods in Molecular Biology series, chapters feature the kind of detailed implementation advice that leads to quality research results. Authoritative and practical, RNA Structure Prediction serves as a valuable guide for both experimental and computational RNA researchers.