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...
| Main Author: | Erciyes, K., |
|---|---|
| Other Authors: | SpringerLink (Online service) |
| Format: | eBook |
| Language: | English |
| Published: |
Cham ; New York :
Springer,
[2015]
|
| Physical Description: |
1 online resource (xvii, 367 pages). |
| Series: |
Computational biology ;
v. 23. |
| Subjects: |
Table of Contents:
- Intro; Preface; Contents; 1 Introduction; 1.1 Introduction; 1.2 Biological Sequences; 1.3 Biological Networks; 1.4 The Need for Distributed Algorithms; 1.5 Outline of the Book; Part IBackground; 2 Introduction to Molecular Biology; 2.1 Introduction; 2.2 The Cell; 2.2.1 DNA; 2.2.2 RNA; 2.2.3 Genes; 2.2.4 Proteins; 2.3 Central Dogma of Life; 2.3.1 Transcription; 2.3.2 The Genetic Code; 2.3.3 Translation; 2.3.4 Mutations; 2.4 Biotechnological Methods; 2.4.1 Cloning; 2.4.2 Polymerase Chain Reaction; 2.4.3 DNA Sequencing; 2.5 Databases; 2.5.1 Nucleotide Databases; 2.5.2 Protein Sequence Databases.
- 2.6 Human Genome Project2.7 Chapter Notes; 3 Graphs, Algorithms, and Complexity; 3.1 Introduction; 3.2 Graphs; 3.2.1 Types of Graphs; 3.2.2 Graph Representations; 3.2.3 Paths, Cycles, and Connectivity; 3.2.4 Trees; 3.2.5 Spectral Properties of Graphs; 3.3 Algorithms; 3.3.1 Time and Space Complexities; 3.3.2 Recurrences; 3.3.3 Fundamental Approaches; 3.3.4 Dynamic Programming; 3.3.5 Graph Algorithms; 3.3.6 Special Subgraphs; 3.4 NP-Completeness; 3.4.1 Reductions; 3.4.2 Coping with NP-Completeness; 3.5 Chapter Notes; 4 Parallel and Distributed Computing; 4.1 Introduction.
- 4.2 Architectures for Parallel and Distributed Computing4.2.1 Interconnection Networks; 4.2.2 Multiprocessors and Multicomputers; 4.2.3 Flynn's Taxonomy; 4.3 Parallel Computing; 4.3.1 Complexity of Parallel Algorithms; 4.3.2 Parallel Random Access Memory Model; 4.3.3 Parallel Algorithm Design Methods; 4.3.4 Shared Memory Programming; 4.3.5 Multi-threaded Programming; 4.3.6 Parallel Processing in UNIX; 4.4 Distributed Computing; 4.4.1 Distributed Algorithm Design; 4.4.2 Threads Re-visited; 4.4.3 Message Passing Interface; 4.4.4 Distributed Processing in UNIX; 4.5 Chapter Notes.
- Part IIBiological Sequences5 String Algorithms; 5.1 Introduction; 5.2 Exact String Matching; 5.2.1 Sequential Algorithms; 5.2.2 Distributed String Matching; 5.3 Approximate String Matching; 5.4 Longest Subsequence Problems; 5.4.1 Longest Common Subsequence; 5.4.2 Longest Increasing Subsequence; 5.5 Suffix Trees; 5.5.1 Construction of Suffix Trees; 5.5.2 Applications of Suffix Trees; 5.5.3 Suffix Arrays; 5.6 Chapter Notes; 6 Sequence Alignment; 6.1 Introduction; 6.2 Problem Statement; 6.2.1 The Objective Function; 6.2.2 Scoring Matrices for Proteins; 6.3 Pairwise Alignment.
- 6.3.1 Global Alignment6.3.2 Local Alignment; 6.4 Multiple Sequence Alignment; 6.4.1 Center Star Method; 6.4.2 Progressive Alignment; 6.5 Alignment with Suffix Trees; 6.6 Database Search; 6.6.1 FASTA; 6.6.2 BLAST; 6.7 Parallel and Distributed Sequence Alignment; 6.7.1 Parallel and Distributed SW Algorithm; 6.7.2 Distributed BLAST; 6.7.3 Parallel/Distributed CLUSTALW; 6.8 Chapter Notes; 7 Clustering of Biological Sequences; 7.1 Introduction; 7.2 Analysis; 7.2.1 Distance and Similarity Measures; 7.2.2 Validation of Cluster Quality; 7.3 Classical Methods; 7.3.1 Hierarchical Algorithms.