Computational Studies Of Rna And Dna

This book integrates modern computational studies of nucleic acids, ranging from advanced electronic structure quantum chemical calculations through explicit solvent molecular dynamics (MD) simulations up to mesoscopic modelling, with the main focus given to the MD field. It gives an equal emphasis to the leading methods and applications while successes as well as pitfalls of the computational techniques are discussed.

This new volume of Methods in Enzymology continues the legacy of this premier serial with quality chapters authored by leaders in the field. This volume covers computational prediction RNA structure and dynamics, including such topics as computational modeling of RNA secondary and tertiary structures, riboswitch dynamics, and ion-RNA, ligand-RNA and DNA-RNA interactions. Continues the legacy of this premier serial with quality chapters authored by leaders in the field Covers computational methods and applications in RNA structure and dynamics Contains chapters with emerging topics such as RNA structure prediction, riboswitch dynamics and thermodynamics, and effects of ions and ligands.

This book represents the most comprehensive and up-to-date collection of information on the topic of computational molecular biology. Bringing the most recent research into the forefront of discussion, Algorithms in Computational Molecular Biology studies the most important and useful algorithms currently being used in the field, and provides related problems. It also succeeds where other titles have failed, in offering a wide range of information from the introductory fundamentals right up to the latest, most advanced levels of study.

Discover the science of biocomputing with this comprehensive and forward-looking new resource DNA- and RNA-Based Computing Systems delivers an authoritative overview of DNA- and RNA-based biocomputing systems that touches on cutting-edge advancements in computer science, biotechnology, nanotechnology, and materials science. Accomplished researcher, academic, and author Evgeny Katz offers readers an examination of the intersection of computational, chemical, materials, and engineering aspects of biomolecular information processing. A perfect companion to the recently published Enzyme-Based Computing by the same editor, the book is an authoritative reference for those who hope to better understand DNA- and RNA-based logic gates, multi-component logic networks, combinatorial calculators, and related computational systems that have recently been developed for use in biocomputing devices. DNA- and RNA-Based Computing Systems summarizes the latest research efforts in this rapidly evolving field and points to possible future research foci. Along with an examination of potential applications in biosensing and bioactuation, particularly in the field of biomedicine, the book also includes topics like: A thorough introduction to the fields of DNA and RNA computing, including DNA/enzyme circuits A description of DNA logic gates, switches and circuits, and how to program them An introduction to photonic logic using DNA and RNA The development and applications of DNA computing for use in databases and robotics Perfect for biochemists, biotechnologists, materials scientists, and bioengineers, DNA- and RNA-Based Computing Systems also belongs on the bookshelves of computer technologists and electrical engineers who seek to improve their understanding of biomolecular information processing. Senior undergraduate students and graduate students in biochemistry, materials science, and computer science will also benefit from this book.

This book is dedicated to the multiple aspects, that is, biological, physical and computational of DNA and RNA molecules. These molecules, central to vital processes, have been experimentally studied by molecular biologists for five decades since the discovery of the structure of DNA by Watson and Crick in 1953. Recent progresses (e.g. use of DNA chips, manipulations at the single molecule level, availability of huge genomic databases...) have revealed an imperious need for theoretical modelling. Further progresses will clearly not be possible without an integrated understanding of all DNA and RNA aspects and studies. The book is intended to be a desktop reference for advanced graduate students or young researchers willing to acquire a broad interdisciplinary understanding of the multiple aspects of DNA and RNA. It is divided in three main sections: The first section comprises an introduction to biochemistry and biology of nucleic acids. The structure and function of DNA are reviewed in R. Lavery's chapter. The next contribution, by V. Fritsch and E. Westhof, concentrates on the folding properties of RNA molecules. The cellular processes involving these molecules are reviewed by J. Kadonaga, with special emphasis on the regulation of transcription. These chapters does not require any preliminary knowledge in the field (except that of elementary biology and chemistry). The second section covers the biophysics of DNA and RNA, starting with basics in polymer physics in the contribution by R. Khokhlov. A large space is then devoted to the presentation of recent experimental and theoretical progresses in the field of single molecule studies. T. Strick's contribution presents a detailed description of the various micro-manipulation techniques, and reviews recent experiments on the interactions between DNA and proteins (helicases, topoisomerases, ...). The theoretical modeling of single molecules is presented by J. Marko, with a special attention paid to the elastic and topological properties of DNA. Finally, advances in the understanding of electrophoresis, a technique of crucial importance in everyday molecular biology, are exposed in T. Duke's contribution. The third section presents provides an overview of the main computational approaches to integrate, analyse and simulate molecular and genetic networks. First, J. van Helden introduces a series of statistical and computational methods allowing the identification of short nucleic fragments putatively involved in the regulation of gene expression from sets of promoter sequences controlling co-expressed genes. Next, the chapter by Samsonova et al. connects this issue of transcriptional regulation with that of the control of cell differentiation and pattern formation during embryonic development. Finally, H. de Jong and D. Thieffry review a series of mathematical approaches to model the dynamical behaviour of complex genetic regulatory networks. This contribution includes brief descriptions and references to successful applications of these approaches, including the work of B. Novak, on the dynamical modelling of cell cycle in different model organisms, from yeast to mammals. . Provides a comprehensive overview of the structure and function of DNA and RNA at the interface between physics, biology and information science.

Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology discusses the latest developments in all aspects of computational biology, bioinformatics, and systems biology and the application of data-analytics and algorithms, mathematical modeling, and simu- lation techniques. • Discusses the development and application of data-analytical and theoretical methods, mathematical modeling, and computational simulation techniques to the study of biological and behavioral systems, including applications in cancer research, computational intelligence and drug design, high-performance computing, and biology, as well as cloud and grid computing for the storage and access of big data sets. • Presents a systematic approach for storing, retrieving, organizing, and analyzing biological data using software tools with applications to general principles of DNA/RNA structure, bioinformatics and applications, genomes, protein structure, and modeling and classification, as well as microarray analysis. • Provides a systems biology perspective, including general guidelines and techniques for obtaining, integrating, and analyzing complex data sets from multiple experimental sources using computational tools and software. Topics covered include phenomics, genomics, epigenomics/epigenetics, metabolomics, cell cycle and checkpoint control, and systems biology and vaccination research. • Explains how to effectively harness the power of Big Data tools when data sets are so large and complex that it is difficult to process them using conventional database management systems or traditional data processing applications. Discusses the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological and behavioral systems. Presents a systematic approach for storing, retrieving, organizing and analyzing biological data using software tools with applications. Provides a systems biology perspective including general guidelines and techniques for obtaining, integrating and analyzing complex data sets from multiple experimental sources using computational tools and software.

Biology is in the midst of a era yielding many significant discoveries and promising many more. Unique to this era is the exponential growth in the size of information-packed databases. Inspired by a pressing need to analyze that data, Introduction to Computational Biology explores a new area of expertise that emerged from this fertile field- the combination of biological and information sciences. This introduction describes the mathematical structure of biological data, especially from sequences and chromosomes. After a brief survey of molecular biology, it studies restriction maps of DNA, rough landmark maps of the underlying sequences, and clones and clone maps. It examines problems associated with reading DNA sequences and comparing sequences to finding common patterns. The author then considers that statistics of pattern counts in sequences, RNA secondary structure, and the inference of evolutionary history of related sequences. Introduction to Computational Biology exposes the reader to the fascinating structure of biological data and explains how to treat related combinatorial and statistical problems. Written to describe mathematical formulation and development, this book helps set the stage for even more, truly interdisciplinary work in biology.

This textbook presents mathematical models in bioinformatics and describes biological problems that inspire the computer science tools used to manage the enormous data sets involved. The first part of the book covers mathematical and computational methods, with practical applications presented in the second part. The mathematical presentation avoids unnecessary formalism, while remaining clear and precise. The book closes with a thorough bibliography, reaching from classic research results to very recent findings. This volume is suited for a senior undergraduate or graduate course on bioinformatics, with a strong focus on mathematical and computer science background.