| Algorithms in Bioinformatics: A Practical Introduction Contributor(s): Sung, Wing-Kin (Author) |
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ISBN: 1420070339 ISBN-13: 9781420070330 Publisher: CRC Press OUR PRICE: $109.25 Product Type: Hardcover - Other Formats Published: December 2009 Annotation: This text focuses on using algorithms and discrete mathematics to solve biological problems. It systematically describes biological applications, the corresponding mathematical/computational problems, and various algorithmic solutions. The author also discusses the practical use of many algorithmic methods and describes what algorithms should be used in different situations. Each chapter contains an overview of the biological problem, a precise definition of the computational problem, a description of various methods, practical issues and further research, references to further reading, and a set of knowledge-testing exercises. Instruction and data for practical exercises are provided on the author's website. |
| Additional Information |
| BISAC Categories: - Science | Life Sciences - Biology - Science | Biotechnology |
| Dewey: 572.802 |
| LCCN: 2009030738 |
| Series: Chapman & Hall/CRC Mathematical and Computational Biology |
| Physical Information: 1" H x 6.2" W x 9.3" (1.55 lbs) 408 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. |