Skip to Content

Handbook of Hidden Markov Models in Bioinformatics

By Martin Gollery

Published June 12th 2008 by Chapman and Hall/CRC – 176 pages

Series: Chapman & Hall/CRC Mathematical & Computational Biology

Purchasing Options:

Description

Demonstrating that many useful resources, such as databases, can benefit most bioinformatics projects, the Handbook of Hidden Markov Models in Bioinformatics focuses on how to choose and use various methods and programs available for hidden Markov models (HMMs).

The book begins with discussions on key HMM and related profile methods, including the HMMER package, the sequence analysis method (SAM), and the PSI-BLAST algorithm. It then provides detailed information about various types of publicly available HMM databases, such as Pfam, PANTHER, COG, and metaSHARK. After outlining ways to develop and use an automated bioinformatics workflow, the author describes how to make custom HMM databases using HMMER, SAM, and PSI-BLAST. He also helps you select the right program to speed up searches. The final chapter explores several applications of HMM methods, including predictions of subcellular localization, posttranslational modification, and binding site.

By learning how to effectively use the databases and methods presented in this handbook, you will be able to efficiently identify features of biological interest in your data.

Reviews

"…a book on how to use software packages based on HMMs for the purpose of doing bioinformatics analyses and database searches. The book’s audience is those who want to use the tools … ."

—Biometrics, December 2008

Contents

Introduction to HMMs and Related Profile Methods

Introduction to Sequence Analysis

Pairwise Algorithms: Smith–Waterman, FASTA, and BLAST

Pairwise Limitations

The Advantages of Profile Methods

The Rise of Profile HMMs

Regular Expressions

But What Exactly Is an HMM?

Curated vs. Noncurated Databases

Disadvantages and Limitations of Profile HMMs for Bioinformatics

Profile HMMs

A General Model HMMs

Plan 7 from Janelia Farms

Local Scoring

Global Alignments

The Maximum Entropy Model

Statistics

Other Uses for HMMs in Biology

HMM Methods

The HMMER Suite of Programs

Creating Multiple Alignments with HMMs

SAM

PSI-BLAST, PSI-TBLASTN, and RPS-BLAST

Regular Expression Methods

MEME and Meta-MEME

Wise2

Commercial and Alternative HMM Implementations

HMMER Options

HMM Databases

The Many Flavors of Pfam

SMART

TIGRfam

SUPERFAMILY

PANTHER

PRED-GPCR

CDD

COG

The TLfam Database

KINfam

PRIAM and metaSHARK

NODE

FPfam

KinasePhos

Building an Analytical Pipeline

What Is an Analytical Pipeline?

How Do I Create a Pipeline and What Do I Put Into It?

Is There An Easier Way to Manage My Workflow?

Are There Any Pipelines That I Can Simply Download and Install?

Building Custom Databases

Building HMMER Databases

Building Databases with the SAM Package

Building PSSM Databases for RPS-BLAST

Building Regular Expression Databases

Speeding Your Searches

Pick Your Targets Carefully

Format Selection

Optimized Solutions

Accelerated Computing

GeneWise

Other Uses of HMMs in Bioinformatics

Methods Comparing HMMs to Other HMMs

Subcellular Localization Prediction

Posttranslational Modification Prediction

Binding Site Predictions

Gene Finding Programs

MEME, MAST, and Meta-MEME

Index

An Introduction, a Summary, and Questions appear in each chapter.

Related Subjects

  1. Bioinformatics

Name: Handbook of Hidden Markov Models in Bioinformatics (Hardback) – Chapman and Hall/CRC 
Description: By Martin Gollery. Demonstrating that many useful resources, such as databases, can benefit most bioinformatics projects, the Handbook of Hidden Markov Models in Bioinformatics focuses on how to choose and use various methods and programs available for hidden Markov models...
Categories: Bioinformatics