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Concepts in Bioinformatics and Genomics takes a conceptual approach to its subject, balancing biology, mathematics, and programming, while highlighting relevant real-world applications. Topics are developed from the fundamentals up like in an introductory textbook. This is a comprehensive bookfor students enrolled in their first course in bioinformatics. A compelling case study gene, the TP53 gene, a human tumor suppressor with strong clinical applications, runs throughout, engaging students with a continuously relevant example.The textbook thoroughly describes basic principles of probability as they lead up to the concept of expectation value (E-value) and its use in sequence alignment programs. Concepts in Bioinformatics and Genomics also describes, from a mathematical perspective, the development of the Hidden MarkovModel and how it can be used to align sequences in multiple sequence alignment programs. Finally, it introduces students to programming exercises directly related to bioinformatics problems. These thought-provoking exercises stretch the students' imaginations and learning, giving them a deeperunderstanding of software programs, molecular biology, basic probability, and program-coding methodology underpinning the discipline. They will have the tools necessary to compute biological data.
This book provides readers with a practical guide covering the full scope of key concepts in bioinformatics, from databases to predictive and comparative algorithms.
This book constitutes the thoroughly refereed post-proceedings of the 31st International Workshop on Graph-Theoretic Concepts in Computer Science, WG 2005, held in Metz, France in June 2005. The 38 revised full papers presented together with 2 invited papers were carefully selected from 125 submissions. The papers provide a wealth of new results for various classes of graphs, graph computations, graph algorithms, and graph-theoretical applications in various fields. The workshop aims at uniting theory and practice by demonstrating how graph-theoretic concepts can be applied to various areas in Computer Science, or by extracting new problems from applications. The goal is to present recent research results and to identify and explore directions of future research.
A comprehensive, authoritative look at an emergent area inpost-genomic science, Evolutionary genomics is an up-and-coming,complex field that attempts to explain the biocomplexity of theliving world. Evolutionary Genomics and Systems Biology isthe first full-length book to blend established and emergingconcepts in bioinformatics, evolution, genomics, and structuralbiology, with the integrative views of network and systems biology. Three key aspects of evolutionary genomics and systems biologyare covered in clear detail: the study of genomic history, i.e.,understanding organismal evolution at the genomic level; the studyof macromolecular complements, which encompasses the evolution ofthe protein and RNA machinery that propels life; and theevolutionary and dynamic study of wiringdiagrams—macromolecular components in interaction—inthe context of genomic complements. The book also features: A solid, comprehensive treatment of phylogenomics, theevolution of genomes, and the evolution of biological networks,within the framework of systems biology A special section on RNA biology—translation, evolutionof structure, and micro RNA and regulation of gene expression Chapters on the mapping of genotypes to phenotypes, the role ofinformation in biology, protein architecture and biologicalfunction, chromosomal rearrangements, and biological networks anddisease Contributions by leading authorities on each topic Evolutionary Genomics and Systems Biology is an idealbook for students and professionals in genomics, bioinformatics,evolution, structural biology, complexity, origins of life,systematic biology, and organismal diversity, as well as thoseindividuals interested in aspects of biological sciences as theyinterface with chemistry, physics, and computer science andengineering.
Concepts and techniques in genomics and proteomics covers the important concepts of high-throughput modern techniques used in the genomics and proteomics field. Each technique is explained with its underlying concepts, and simple line diagrams and flow charts are included to aid understanding and memory. A summary of key points precedes each chapter within the book, followed by detailed description in the subsections. Each subsection concludes with suggested relevant original references. Provides definitions for key concepts Case studies are included to illustrate ideas Important points to remember are noted
Biomedicine is one of the most important fields for the prospective applications of the information from human genome studies. However, there are many 'white spots' in the present-day understanding of the biomedical implications of this information. Given that at least half of the proteins in the established sequence of the human genome have no annotation whatsoever and that the sequence similarity searches are not likely to produce any, definite research strategies to analyse the functions of these unknown proteins as well as other enigmatic aspects of the human genome are being elaborated. The elaboration of the logistics of these research strategies, of the relevant computational methodologies as well as the general management of the informational complexity of the biological systems belong to the main tasks for the post-genomic bioinformatics. This volume concentrates on the role of the biophysical studies and biophysical concepts that can assist the endeavour.
Thoroughly Describes Biological Applications, Computational Problems, and Various Algorithmic Solutions Developed from the author’s own teaching material, Algorithms in Bioinformatics: A Practical Introduction provides an in-depth introduction to the algorithmic techniques applied in bioinformatics. For each topic, the author clearly details the biological motivation and precisely defines the corresponding computational problems. He also includes detailed examples to illustrate each algorithm and end-of-chapter exercises for students to familiarize themselves with the topics. Supplementary material is available at http://www.comp.nus.edu.sg/~ksung/algo_in_bioinfo/ This classroom-tested textbook begins with basic molecular biology concepts. It then describes ways to measure sequence similarity, presents simple applications of the suffix tree, and discusses the problem of searching sequence databases. After introducing methods for aligning multiple biological sequences and genomes, the text explores applications of the phylogenetic tree, methods for comparing phylogenetic trees, the problem of genome rearrangement, and the problem of motif finding. It also covers methods for predicting the secondary structure of RNA and for reconstructing the peptide sequence using mass spectrometry. The final chapter examines the computational problem related to population genetics.

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