Handbook of hidden Markov models in bioinformatics /

Handbook of hidden Markov models in bioinformatics /

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Bibliographic Details
Author / Creator:Gollery, Martin.
Imprint:Boca Raton : CRC Press, c2008.
Description:xix, 156 p. : ill. ; 25 cm. + 1 CD-ROM (4 3/4 in.).
Language:English
Series:Chapman & Hall/CRC mathematical and computational biology series
Chapman and Hall/CRC mathematical & computational biology series.
Subject:
Bioinformatics.
Computational biology.
Markov processes.
Bioinformatics.
Computational biology.
Markov processes.
Format: Print Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/7920830
Hidden Bibliographic Details
ISBN:9781584886846 (hardback : alk. paper)
1584886846 (hardback : alk. paper)
Notes:"A Chapman & Hall book."
Includes bibliographical references and index.
System requirements: HMMer, SAM, ClustalW, Interproscan, PSI-BLAST, Pfam, HHsearch, SCOOP.
Table of Contents:
  • Foreword
  • Preface
  • Acknowledgments
  • About the Author
  • 1. Introduction to HMMs and Related Profile Methods
  • 1.1. Introduction
  • 1.2. Introduction to Sequence Analysis
  • 1.3. Pairwise Algorithms-Smith-Waterman, FASTA and BLAST
  • 1.4. Pairwise Limitations
  • 1.5. The Advantages of Profile Methods
  • 1.6. The Rise of Profile-HMMs
  • 1.7. Regular Expressions
  • 1.8. But What Exactly is an HMM?
  • 1.9. Curated vs. Non-Curated Databases
  • 1.10. Disadvantages and Limitations of Profile-HMMs for Bioinformatics
  • 1.11. Summary
  • 1.12. Questions
  • References
  • 2. Profile HMM Models
  • 2.1. Introduction
  • 2.2. A General Model for HMMs
  • 2.3. Plan 7 from Janelia Farms
  • 2.4. Local Scoring
  • 2.5. Global Alignments
  • 2.5.1. Calculating Transition Probabilities
  • 2.5.2. State Probabilities
  • 2.5.3. Building a Better Model
  • 2.6. The Maximum Entropy Model
  • 2.7. Statistics
  • 2.8. Other Uses for HMMs in Biology
  • 2.9. Summary
  • 2.10. Questions
  • References
  • 3. HMM Methods
  • 3.1. Introduction
  • 3.1.1. What Exactly Do You Want to Do?
  • 3.2. The HMMer Suite of Programs
  • 3.3. Creating Multiple Alignments with HMMs
  • 3.3.1. HMMer Statistics
  • 3.3.2. Sequence Scores and Domain Scores
  • 3.3.3. HMMer Format
  • 3.4. SAM
  • 3.5. PSI-BLAST, PSI-TBLASTN and RPS-BLAST
  • 3.6. Regular Expression Methods
  • 3.7. MEME and Meta-MEME
  • 3.8. Wise2
  • 3.9. Commercial and Alternative HMM Implementations
  • 3.10. HMMer Options
  • 3.10.1. HMMPfam
  • 3.11. Summary
  • 3.12. Questions
  • References
  • 4. HMM Databases
  • 4.1. Introduction
  • 4.2. The Many Flavors of Pfam
  • 4.3. SMART
  • 4.4. TIGRFAM
  • 4.5. SUPERFAMILY
  • 4.6. PANTHER
  • 4.7. PRED-GPCR
  • 4.8. The Conserved Domain Database, CDD
  • 4.9. COG
  • 4.9.1. KOGs and TWOGs
  • 4.10. The TLFAM Database
  • 4.11. KinFam
  • 4.12. PRIAM and MetaSHARK
  • 4.13. NODE
  • 4.14. FPfam
  • 4.15. KinasePhos
  • 4.16. Summary
  • 4.17. Questions
  • References
  • 5. Building an Analytical Pipeline
  • 5.1. Introduction
  • 5.2. What Is an Analytical Pipeline?
  • 5.3. How Do I Create a Pipeline, and What Do I Put into it?
  • 5.4. Is There an Easier Way To Manage My Workflow?
  • 5.4.1. What to Look for in a Workflow Development Tool
  • 5.5. Are There Any Pipelines That I Can Simply Download and Install?
  • 5.5.1. InterProScan
  • 5.5.2. InterPro Content
  • 5.5.3. PartiGene
  • 5.6. Summary
  • 5.7. Questions
  • References
  • 6. Building Custom Databases
  • 6.1. Introduction
  • 6.2. Building HMMer Databases
  • 6.2.1. Calibration of the Model
  • 6.3. Building Databases with the SAM Package
  • 6.3.1. Inherent Differences between SAM and HMMer
  • 6.4. Building PSSM Databases for RPS-BLAST
  • 6.5. Building Regular Expression Databases
  • 6.6. Summary
  • 6.7. Questions
  • References
  • 7. Speeding Your Searches
  • 7.1. Introduction
  • 7.2. Pick Your Targets Carefully
  • 7.2.1. Target Triage
  • 7.2.2. Data Distillation Column
  • 7.3. Format Selection
  • 7.4. Optimized Solutions
  • 7.4.1. MPI-HMMer
  • 7.4.2. SledgeHMMer
  • 7.4.3. ClawHMMer
  • 7.4.4. JackHMMer
  • 7.4.5. Commercially Available Solutions
  • 7.5. Accelerated Computing
  • 7.6. GeneWise
  • 7.7. Summary
  • 7.8. Questions
  • References
  • 8. Other Uses of HMMs in Bioinformatics
  • 8.1. Introduction
  • 8.2. Methods Comparing HMMs to Other HMMs
  • 8.2.1. PRC
  • 8.2.2. HHsearch
  • 8.2.3. SCOOP
  • 8.2.4. More Profile Comparison Systems
  • 8.3. Subcellular Localization Prediction
  • 8.4. Post-Translational Modification Prediction
  • 8.5. Binding Site Predictions
  • 8.6. Gene Finding Programs
  • 8.7. MEME, MAST and MetaMEME
  • 8.7.1. MAST (Motif Alignment and Search Tool)
  • 8.7.2. Meta-MEME
  • 8.7.3. Meta-MEME Programs
  • 8.8. ClustalW
  • 8.8.1. Advanced ClustalW Options
  • 8.9. Summary
  • 8.10. Questions
  • References
  • Index
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