Lenwood S Heath

Problem Solving Handbook in Computational Biology and Bioinformatics Lenwood S Heath 2011 edition

Marc Notes: Includes bibliographical references and index. Brief Description: Bioinformatics is constantly evolving, but a core body of algorithmic ideas for a problem-solving approach in the field has emerged. This handbook stresses that approach as it covers all relevant areas of computational biology and bioinformatics. Review Quotes: From the reviews: The editors of this handbook have collect(ed) together, in one place, the algorithms and methods that form the modern bioinformatician s toolkit. Each chapter contains an introduction to the respective topic, detailed descriptions of the relevant algorithmic methods, software implementations, and applications, and concludes with advanced topics. this handbook provides some value for researchers and practitioners in the field. In summary, for most of the topics covered, this book complements the standard textbooks in a useful way. (Gunnar Klau, ACM Computing Reviews, June, 2011) Review Quotes: From the reviews: The editors of this handbook have collect(ed) together, in one place, the algorithms and methods that form the modern bioinformatician s toolkit. Each chapter contains an introduction to the respective topic, detailed descriptions of the relevant algorithmic methods, software implementations, and applications, and concludes with advanced topics. this handbook provides some value for researchers and practitioners in the field. In summary, for most of the topics covered, this book complements the standard textbooks in a useful way. (Gunnar Klau, ACM Computing Reviews, June, 2011)"Table of Contents: Part I. Sequences -- Modern BLAST Programs / Jian Ma, Louxin Zhang -- 1. Introduction -- 2. Available Implementations -- 3. Algorithm Description -- 4. BLAST Statistics -- 5. Examples -- 6. Advanced Topics -- 7. Exercises -- 8. Further Reading -- References -- Practical Multiple Sequence Alignment / Tobias Rausch, Knut Reinert -- 1. History of the Problem -- 2. Algorithm Description -- 3. Available Implementations -- 4. Advanced Topics -- 5. Exercises -- 6. Further Reading -- References -- Sequence Alignment Statistics / John L. Spouge -- 1. Introduction -- 2. Dynamic Programming with Independent Random Inputs -- 3. The Extreme-Value Distributions for Maxima -- 4. The Poisson Approximation for Counting Rare Events -- 5. Pairwise Sequence Alignment -- 6. Islands in Local Alignment -- 7. The Finite-Size Correction in Gapped Local Alignment -- 8. The Independent Diagonals Approximation -- 9. The Combinatorial Approximation -- References -- Part II. Phylogenetics -- Practical Implications of Coalescent Theory / Paul Marjoram, Paul Joyce -- 1. Introduction - What is the coalescent? -- 2. Motivating Problems -- 3. Implications of the Coalescent -- 4. Software Review -- 5. Further Reading -- 6. Exercises for the reader -- References -- Graph Model of Coalescence with Recombinations / Laxmi Parida -- 1. Introduction -- 2. Random Graph Framework: Pedigree Graph -- 3. Pedigree Subgraphs -- 4. Unilinear Transmission: Monochromatic Subgraphs -- 5. Genetic Exchange Model: Mixed Subgraph -- 6. Topological definition of GMRCA: Least Common Ancestor with Ancestry (LCAA) -- 7. Discussion -- References -- Phylogenetic Trees From Sequences / Paul Ryvkin, Li-San Wang -- 1. Basics -- 2. Sequence evolution -- 3. Distance-based phylogeny reconstruction -- 4. Maximum parsimony -- 5. Maximum likelihood -- 6. Multiple phylogenies: comparison, consensus, and confidence -- 7. Software -- 8. Further reading -- 9. Exercise -- References -- Evolutionary Phylogenetic Networks: Models and Issues / Luay Nakhleh -- 1. Introduction -- 2. Phylogenetic Networks and the Trees Within -- 3. Optimization Criteria for Inferring and Evaluating Phylogenetic Networks -- 4. To Network, or Not to Network, That Is the Question -- 5. Exercises -- 6. Further Reading -- References -- Genome Wide Association Studies / Paola Sebastiani, Nadia Solovieff -- 1. An overview of population genetics -- 2. Genome-Wide Association Studies -- 3. Resources -- 4. Advanced Topics -- 5. Exercise -- References -- Part III. Proteins: Structure, Function, and Biochemistry -- Novel Perspectives on Protein Structure Prediction / Bonnie Berger, Jerome Waldispuhl -- 1. Introduction -- 2. Modeling transmembrane ?-barrel structure -- 3. Energy model -- 4. Algorithms -- 5. Applications -- 6. Sampling the local neighborhood of 3D structures -- 7. Exercises -- 8. Further reading -- References -- Stochastic Simulation for Biochemical Systems / Yang Cao -- 1. History of the Problem -- 2. Algorithm Description -- 3. Available Implementations -- 4. Examples -- 5. Advanced Topics -- 6. Exercises -- 7. Further Reading -- References -- Part IV. Networks -- Cellular Response Networks / Christopher D. Lasher, Christopher L. Poirel, T. M. Murali -- 1. History of the Problem -- 2. Algorithm Descriptions -- 3. Available Implementations -- 4. Examples -- 5. Advanced Topics: Comparing Response Networks -- 6. Exercises -- 7. Outlook and Further Reading -- References -- Identification of Modules in Protein-Protein Interaction Networks / Sinan Erten, Mehmet Koyuturk -- 1. History of the Problem -- 2. Algorithm Description -- 3. Available Implementations -- 4. Examples -- 5. Advanced Topics -- 6. Exercises -- 7. Further Reading -- References -- Part V. Biological Data Management and Mining -- Designing Microarray Experiments / Paola Sebastiani, Jacqui Milton, Ling Wang -- 1. Designed experiments versus observational studies -- 2. Discovery of Differentially Expressed Genes -- 3. Building prognostic models -- 4. Running the experiment -- 5. Advanced topics and further reading -- 6. Exercise -- References -- Matrix and Tensor Decompositions / Karthik Devarajan -- 1. Introduction -- 2. Non-negative Matrix Factorization -- 3. Singular Value Decomposition -- 4. Other Matrix Decompositions -- 5. Comparison of the Methods -- 6. Tensor Decompositions -- 7. Concluding Remarks -- 8. Exercises -- References -- Practical Applications of the Gene Ontology Resource / Rachael P. Huntley, Emily C. Dimmer, Rolf Apweiler -- 1. Introduction -- 2. GO Annotations -- 3. Viewing the GO and its annotations -- 4. Use of GO in the literature -- 5. Popular methods for supplementing and grouping GO annotations -- 6. The effective use of GO for large-scale analyses -- 7. Exercises -- 8. Further Reading -- References -- Index.