Compact Handbook Of Computational Biology

The assimilation of computational methods into the life sciences has played an important role in advancing biological research. From sequencing genomes to discovering motifs in large collections of functionally equivalent sequences of nucleic acids and proteins, the value of powerful computational tools has become abundantly clear. The Compact Hand

The enormous complexity of biological systems at the molecular level must be answered with powerful computational methods. Computational biology is a young field, but has seen rapid growth and advancement over the past few decades. Surveying the progress made in this multidisciplinary field, the Handbook of Computational Molecular Biology of

Written with the advanced undergraduate in mind, this book introduces into the field of Bioinformatics. The authors explain the computational and conceptional background to the analysis of large-scale sequence data. Many of the corresponding analysis methods are rooted in evolutionary thinking, which serves as a common thread throughout the book. The focus is on methods of comparative genomics and subjects covered include: alignments, gene finding, phylogeny, and the analysis of single nucleotide polymorphisms (SNPs). The volume contains exercises, questions & answers to selected problems.

Bioinformatics is growing by leaps and bounds; theories/algorithms/statistical techniques are constantly evolving. Nevertheless, a core body of algorithmic ideas have emerged and researchers are beginning to adopt a "problem solving" approach to bioinformatics, wherein they use solutions to well-abstracted problems as building blocks to solve larger scope problems. Problem Solving Handbook for Computational Biology and Bioinformatics is an edited volume contributed by world renowned leaders in this field. This comprehensive handbook with problem solving emphasis, covers all relevant areas of computational biology and bioinformatics. Web resources and related themes are highlighted at every opportunity in this central easy-to-read reference. Designed for advanced-level students, researchers and professors in computer science and bioengineering as a reference or secondary text, this handbook is also suitable for professionals working in this industry.

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.

Numerous fascinating breakthroughs in biotechnology have generated large volumes and diverse types of high throughput data that demand the development of efficient and appropriate tools in computational statistics integrated with biological knowledge and computational algorithms. This volume collects contributed chapters from leading researchers to survey the many active research topics and promote the visibility of this research area. This volume is intended to provide an introductory and reference book for students and researchers who are interested in the recent developments of computational statistics in computational biology.

An introduction to the world of bioinformatics Massive increases in computing power and the ability to routinely sequence whole genomes of living organisms have begun to fundamentally alter our understanding of biology, medicine, and agriculture. At the intersection of the growing information and genomics revolutions sits bioinformatics, which uses modern computational power to reveal patterns in biological data sets, especially DNA, RNA, and protein sequences. Computational Biology: A Hypertextbook, by Scott Kelley and Dennis Didulo, provides a wonderful introduction for anyone who wants to learn the basics of bioinformatics. This book is more than a textbook because of the wealth of online ancillary materials and how the print and electronic components are integrated to form a complete educational resource. Aspects that make Computational Biology: A Hypertextbook a unique and valuable tool for teaching and learning bioinformatics include Clear explanations of the basic biology of DNA, RNA, and proteins and how the related bioinformatics algorithms work Extensive exercises that enable students to practice with the same bioinformatics applications that are used by scientists worldwide Tutorials, sample data sets, and interactive learning tools developed with teachers in mind and field-tested by hundreds of students Online tutorials and curated web links that are accurate (instead of frustrating!) and won't lead to dead ends Online resources that work on multiple platforms and electronic devices Computational Biology: A Hypertextbook is written in an accessible voice, punctuated with humor, and designed to significantly increase computational competencies. Biology and computer science undergraduate and graduate students will thoroughly enjoy learning from this unique hypertextbook, as will anyone with an interest in exploring this burgeoning topic.