Distributed and Sequential Algorithms for Bioinformatics

This unique textbook/reference presents unified coverage of bioinformatics topics relating to both biological sequences and biological networks, providing an in-depth analysis of cutting-edge distributed algorithms, as well as of relevant sequential algorithms. In addition to introducing the latest algorithms in this area, more than fifteen new distributed algorithms are also proposed. Topics and features: reviews a range of open challenges in biological sequences and networks; describes in detail both sequential and parallel/distributed algorithms for each problem; suggests approaches for distributed algorithms as possible extensions to sequential algorithms, when the distributed algorithms for the topic are scarce; proposes a number of new distributed algorithms in each chapter, to serve as potential starting points for further research; concludes each chapter with self-test exercises, a summary of the key points, a comparison of the algorithms described, and a literature review.

Provides a comprehensive survey of distributed algorithms for bioinformatics problems Includes sequential and distributed algorithms for both DNA sequences and biological networks Covers the key features of fundamental algorithms for bioinformatics without sacrificing theoretical content Includes supplementary material: sn.pub/extras

Autorentext

Dr. K. Erciyes is Rector of Izmir University, Turkey, where he also serves as a professor in the Computer Engineering Department. His other publications include the Springer title Distributed Graph Algorithms for Computer Networks.

Inhalt

Introduction.- Part I: Background.- Introduction to Molecular Biology.- Graphs, Algorithms and Complexity.- Parallel and Distributed Computing.- Part II: Biological Sequences.- String Algorithms.- Sequence Alignment.- Clustering of Biological Sequences.- Sequence Repeats.- Genome Analysis.- Part III: Biological Networks.- Analysis of Biological Networks.- Cluster Discovery in Biological Networks.- Network Motif Search.- Network Alignment.- Phylogenetics.- Epilogue.