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Pattern discovery in bioinformatics : theory & algorithms / Laxmi Parida.

Laxmi Parida

Boca Raton : Chapman & Hall/CRC, 2008.

Online access

  • Title:
    Pattern discovery in bioinformatics : theory & algorithms / Laxmi Parida.
  • Author: Laxmi Parida
  • Subjects: Bioinformatics; Pattern recognition systems; Computational biology; Computational Biology -- methods; Pattern Recognition, Automated; COMPUTERS -- Bioinformatics; Bioinformatics; Computational biology; Pattern recognition systems; Electronic books;
    Dewey: 572.80285
  • Rights: Terms governing use: Copyright.
    Access restrictions: NON_PRINT_LEGAL_DEPOSIT
  • Publication Details: Boca Raton : Chapman & Hall/CRC, 2008.
  • Language: English
  • Description: Contents: INTRODUCTION
    Ubiquity of Patterns
    Motivations Form Biology
    The Need for Rigor
    Who Is a Reader of This Book?


    THE FUNDAMENTALS
    BASIC ALGORITHMICS
    Introduction
    Graphs
    Tree Problem 1: (Minimum Spanning Tree)
    Tree Problem 2: (Steiner Tree)
    Tree Problem 3: (Minimum Mutation Labeling)
    Storing and Retrieving Elements
    Asymptotic Functions
    Recurrence Equations
    NP-Complete Class of Problems

    BASIC STATISTICS
    Introduction
    Basic Probability
    The Bare Truth about Inferential Statistics
    Summary

    WHAT ARE PATTERNS?
    Introduction
    Common Thread
    Pattern Duality
    Irredundant Patterns
    Constrained Patterns
    When Is a Pattern Specification Non-Trivial?
    Classes of Patterns


    PATTERNS ON LINEAR STRINGS
    MODELING THE STREAM OF LIFE
    Introduction
    Modeling a Biopolymer
    Bernoulli Scheme
    Markov Chain
    Hidden Markov Model (HMM)
    Comparison of the

    Contents: Schemes
    Conclusion

    STRING PATTERN SPECIFICATIONS
    Introduction
    Notation
    Solid Patterns
    Rigid Patterns
    Extensible Patterns
    Generalizations

    ALGORITHMS AND PATTERN STATISTICS
    Introduction
    Discovery Algorithm
    Pattern Statistics
    Rigid Patterns
    Extensible Patterns
    Measure of Surprise
    Applications

    MOTIF LEARNING
    Introduction: Local Multiple Alignment
    Probabilistic Model: Motif Profile
    The Learning Problem
    Importance Measure
    Algorithms to Learn a Motif Profile
    An Expectation Maximization Framework
    A Gibbs Sampling Strategy
    Interpreting the Motif Profile in Terms of p

    THE SUBTLE MOTIF
    Introduction: Consensus Motif
    Combinatorial Model: Subtle Motif
    Distance between Motifs
    Statistics of Subtle Motifs
    Performance Score
    Enumeration Schemes
    A Combinatorial Algorithm
    A Probabilistic Algorithm
    A Modular Solution
    Conclusion


    PATTERNS ON

    Contents: META-DATA
    PERMUTATION PATTERNS
    Introduction
    Notation
    How Many Permutation Patterns?
    Maximality
    Parikh Mapping-Based Algorithm
    Intervals
    Intervals to PQ Trees
    Applications
    Conclusion

    PERMUTATION PATTERN PROBABILITIES
    Introduction
    Unstructured Permutations
    Structured Permutations

    TOPOLOGICAL MOTIFS
    Introduction
    What Are Topological Motifs?
    The Topological Motif
    Compact Topological Motifs
    The Discovery Method
    Related Classical Problems
    Applications
    Conclusion

    SET-THEORETIC ALGORITHMIC TOOLS
    Introduction
    Some Basic Properties of Finite Sets
    Partial Order Graph G(S, E) of Sets
    Boolean Closure of Sets
    Consecutive (Linear) Arrangement of Set Members
    Maximal Set Intersection Problem (maxSIP)
    Minimal Set Intersection Problem (minSIP)
    Multi-Sets
    Adapting the Enumeration Scheme

    EXPRESSION AND PARTIAL ORDER MOTIFS
    Introduction
    Extracting (monotone CNF)

    Contents: Boolean Expressions
    Extracting Partial Orders
    Statistics of Partial Orders
    Redescriptions
    Application: Partial Order of Expressions
    Summary

    REFERENCES

    INDEX

    Exercises appear at the end of every chapter.

  • Identifier: ISBN 9781420010732 (electronic bk.); ISBN 1420010735 (electronic bk.); BNB GBB7C5279; System number: 018424024
  • Notes: Bibliography note: Includes bibliographical references (pages 503-513) and index.
  • Physical Description: 1 online resource (526 pages) : illustrations.
  • Series: Chapman & Hall/CRC mathematical and computational biology series
  • Shelfmark(s): General Reference Collection DRT ELD.DS.157606
  • UIN: BLL01018424024

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