Pattern Recognition in Computational Molecular Biology : Techniques and Approaches

Pattern Recognition in Computational Molecular Biology : Techniques and Approaches / Mourad Elloumi, Costas Iliopoulos, Jason T.L. Wang, Albert Y. Zomaya.

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Bibliographic Details
Main Authors: Elloumi, Mourad (Author), Iliopoulos, Costas (Author), Wang, Jason T. L. (Author), Zomaya, Albert Y. (Author)
Format: eBook
Language:English
Published: Wiley, 2015.
Edition:1st
Subjects:
Molecular biology > Data processing.
Computational biology.
Pattern recognition systems.
TECHNOLOGY & ENGINEERING > Electronics > Digital.
Computational biology
Molecular biology > Data processing
Pattern recognition systems
Online Access:Click for online access
Table of Contents:
  • Wiley Series; Title Page; Copyright; Table of Contents; List of Contributors; Preface; Part 1: Pattern Recognition in Sequences; Chapter 1: Combinatorial Haplotyping Problems; 1.1 Introduction; 1.2 Single Individual Haplotyping; 1.3 Population Haplotyping; References; Chapter 2: Algorithmic Perspectives of the String Barcoding Problems; 2.1 Introduction; 2.2 Summary of Algorithmic Complexity Results for Barcoding Problems; 2.3 Entropy-Based Information Content Technique for Designing Approximation Algorithms for String Barcoding Problems.
  • 2.4 Techniques for Proving Inapproximability Results for String Barcoding Problems2.5 Heuristic Algorithms for String Barcoding Problems; 2.6 Conclusion; Acknowledgments; References; Chapter 3: Alignment-Free Measures for Whole-Genome Comparison; 3.1 Introduction; 3.2 Whole-Genome Sequence Analysis; 3.3 Underlying Approach; 3.4 Experimental Results; 3.5 Conclusion; Author's Contributions; 3.6 Acknowledgments; References; Chapter 4: A Maximum Likelihood Framework for Multiple Sequence Local Alignment; 4.1 Introduction; 4.2 Multiple Sequence Local Alignment; 4.3 Motif Finding Algorithms.
  • 4.4 Time Complexity4.5 Case Studies; 4.6 Conclusion; References; Chapter 5: Global Sequence Alignment with a Bounded Number of Gaps; 5.1 Introduction; 5.2 Definitions and Notation; 5.3 Problem Definition; 5.4 Algorithms; 5.5 Conclusion; References; Part 2: Pattern Recognition in Secondary Structures; Chapter 6: A Short Review on Protein Secondary Structure Prediction Methods; 6.1 Introduction; 6.2 Representative Protein Secondary Structure Prediction Methods; 6.3 Evaluation of Protein Secondary Structure Prediction Methods; 6.4 Conclusion; Acknowledgments; References.
  • Chapter 7: A Generic Approach to Biological Sequence Segmentation Problems: Application to Protein Secondary Structure Prediction7.1 Introduction; 7.2 Biological Sequence Segmentation; 7.3 MSVMpred; 7.4 Postprocessing with A Generative Model; 7.5 Dedication to Protein Secondary Structure Prediction; 7.6 Conclusions and Ongoing Research; Acknowledgments; References; Chapter 8: Structural Motif Identification and Retrieval: A Geometrical Approach; 8.1 Introduction; 8.2 A Few Basic Concepts; 8.3 State of The Art; 8.4 A Novel Geometrical Approach to Motif Retrieval; 8.5 Implementation Notes.
  • 8.6 Conclusions and Future WorkAcknowledgment; References; Chapter 9: Genome-Wide Search for Pseudoknotted Noncoding RNA: A Comparative Study; 9.1 Introduction; 9.2 Background; 9.3 Methodology; 9.4 Results and Interpretation; 9.5 Conclusion; References; Part 3: Pattern Recognition in Tertiary Structures; Chapter 10: Motif Discovery in Protein 3D-Structures using Graph Mining Techniques; 10.1 Introduction; 10.2 From Protein 3D-Structures to Protein Graphs; 10.3 Graph Mining; 10.4 Subgraph Mining; 10.5 Frequent Subgraph Discovery; 10.6 Feature Selection; 10.7 Feature Selection for Subgraphs.

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