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9781852336714

Data Mining in Bioinformatics

by ; ; ;
  • ISBN13:

    9781852336714

  • ISBN10:

    1852336714

  • Format: Hardcover
  • Copyright: 2004-10-01
  • Publisher: Springer Verlag

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Supplemental Materials

What is included with this book?

Summary

The goal of this book is to help readers understand state-of-the-art techniques in biological data mining and data management and includes topics such as: - preprocessing tasks such as data cleaning and data integration as applied to biological data - classification and clustering techniques for microarrays - comparison of RNA structures based on string properties and energetics - discovery of the sequence characteristics of different parts of the genome - mining of haplotypes to find disease markers - sequencing of events leading to the folding of a protein - inference of the subcellular location of protein activity - classification of chemical compounds based on structure - special purpose metrics and index structures for phylogenetic applications - a new query language for protein searching based on the shape of proteins - very fast indexing schemes for sequences and pathways Aimed at computer scientists, necessary biology is explained.

Table of Contents

Contributors ix
Part I. Overview
1(40)
Introduction to Data Mining in Bioinformatics
3(6)
Background
3(1)
Organization of the Book
4(4)
Support on the Web
8(1)
Survey of Biodata Analysis from a Data Mining Perspective
9(32)
Introduction
9(3)
Data Cleaning, Data Preprocessing, and Data Integration
12(4)
Exploration of Data Mining Tools for Biodata Analysis
16(5)
Discovery of Frequent Sequential and Structured Patterns
21(3)
Classification Methods
24(1)
Cluster Analysis Methods
25(3)
Computational Modeling of Biological Networks
28(3)
Data Visualization and Visual Data Mining
31(4)
Emerging Frontiers
35(3)
Conclusions
38(3)
Part II. Sequence and Structure Alignment
41(42)
AntiClust A1: Multiple Sequence Alignment by Antipole Clustering
43(16)
Introduction
43(2)
Related Work
45(2)
Antipole Tree Data Structure for Clustering
47(1)
AntiClustA1: Multiple Sequence Alignment via Antipoles
48(3)
Comparing ClustalW and AntiClustA1
51(2)
Case Study
53(1)
Conclusions
54(2)
Future Developments and Research Problems
56(3)
RNA Structure Comparison and Alignment
59(24)
Introduction
59(1)
RNA Structure Comparison and Alignment Models
60(7)
Hardness Results
67(1)
Algorithms for RNA Secondary Structure Comparison
67(4)
Algorithms for RNA Structure Alignment
71(5)
Some Experimental Results
76(7)
Part III. Biological Data Mining
83(134)
Piecewise Constant Modeling of Sequential Data Using Reversible Jump Markov Chain Monte Carlo
85(20)
Introduction
85(3)
Bayesian Approach and MCMC Methods
88(6)
Examples
94(8)
Concluding Remarks
102(3)
Gene Mapping by Pattern Discovery
105(22)
Introduction
105(1)
Gene Mapping
106(4)
Haplotype Patterns as a Basis for Gene Mapping
110(7)
Instances of the Generalized Algorithm
117(7)
Related Work
124(1)
Discussion
124(3)
Predicting Protein Folding Pathways
127(16)
Introduction
127(2)
Preliminaries
129(3)
Predicting Folding Pathways
132(5)
Pathways for Other Proteins
137(4)
Conclusions
141(2)
Data Mining Methods for a Systematics of Protein Subcellular Location
143(46)
Introduction
144(3)
Methods
147(39)
Conclusion
186(3)
Mining Chemical Compounds
189(28)
Introduction
189(2)
Background
191(2)
Related Research
193(3)
Classification Based on Frequent Subgraphs
196(8)
Experimental Evaluation
204(9)
Conclusions and Directions for Future Research
213(4)
Part IV. Biological Data Management
217(80)
Phyloinformatics: Toward a Phylogenetic Database
219(24)
Introduction
219(3)
What Is a Phylogenetic Database For?
222(2)
Taxonomy
224(5)
Tree Space
229(1)
Synthesizing Bigger Trees
230(4)
Visualizing Large Trees
234(1)
Phylogenetic Queries
234(5)
Implementation
239(1)
Prospects and Research Problems
240(3)
Declarative and Efficient Querying on Protein Secondary Structures
243(32)
Introduction
243(3)
Protein Format
246(1)
Query Language and Sample Queries
246(2)
Query Evaluation Techniques
248(4)
Query Optimizer and Estimation
252(15)
Experimental Evaluation and Application of Periscope/PS2
267(4)
Conclusions and Future Work
271(4)
Scalable Index Structures for Biological Data
275(22)
Introduction
275(2)
Index Structure for Sequences
277(3)
Indexing Protein Structures
280(3)
Comparative and Integrative Analysis of Pathways
283(12)
Conclusion
295(2)
Glossary 297(6)
References 303(24)
Biographies 327(10)
Index 337

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What is included with this book?

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