Current Protocols in Bioinformatics

Copyright © 1999-2012 by John Wiley and Sons, Inc. All Rights Reserved.

Current Protocols in Bioinformatics

Online ISBN: 9780471250951

DOI: 10.1002/0471250953

Browse by Table of Contents

  1. Foreword
  2. Preface
  3. Chapter 1 Using Biological Databases
    1. Unit 1.1 The Importance of Biological Databases in Biological Discovery
    2. Unit 1.2 Searching Online Mendelian Inheritance in Man (OMIM) for Information on Genetic Loci Involved in Human Disease
    3. Unit 1.3 Searching NCBI Databases Using Entrez
    4. Unit 1.4 The UCSC Genome Browser
    5. Unit 1.5 Using the NCBI Map Viewer to Browse Genomic Sequence Data
    6. Unit 1.6 Using the DFCI Gene Index Databases for Biological Discovery
    7. Unit 1.7 Searching the Mouse Genome Informatics (MGI) Resources for Information on Mouse Biology from Genotype to Phenotype
    8. Unit 1.8 Searching WormBase for Information about Caenorhabditis elegans
    9. Unit 1.9 Using the Tools and Resources of the RCSB Protein Data Bank
    10. Unit 1.10 Human Mutation Databases
    11. Unit 1.11 Using The Arabidopsis Information Resource (TAIR) to Find Information About Arabidopsis Genes
    12. Unit 1.12 Using the KEGG Database Resource
    13. Unit 1.13 The Human Gene Mutation Database (HGMD) and Its Exploitation in the Fields of Personalized Genomics and Molecular Evolution
    14. Unit 1.14 Exploring Genetic, Genomic, and Phenotypic Data at the Rat Genome Database
    15. Unit 1.15 Using the Ensembl Genome Server to Browse Genomic Sequence Data
    16. Unit 1.16 Using the iHOP Information Resource to Mine the Biomedical Literature on Genes, Proteins, and Chemical Compounds
    17. Unit 1.17 Using the MetaCyc Pathway Database and the BioCyc Database Collection
    18. Unit 1.18 Exploring Zebrafish Genomic, Functional and Phenotypic Data Using ZFIN
    19. Unit 1.19 Searching NCBI's dbSNP Database
    20. Unit 1.20 Using the Saccharomyces Genome Database (SGD) for Analysis of Genomic Information
    21. Unit 1.21 Access Guide to Human Proteinpedia
  4. Chapter 2 Recognizing Functional Domains
    1. Unit 2.1 An Introduction to Recognizing Functional Domains
    2. Unit 2.2 Using the Blocks Database to Recognize Functional Domains
    3. Unit 2.3 Multiple Sequence Alignment Using ClustalW and ClustalX
    4. Unit 2.4 Discovering Novel Sequence Motifs with MEME
    5. Unit 2.5 Identifying Protein Domains with the Pfam Database
    6. Unit 2.6 Using TESS to Predict Transcription Factor Binding Sites in DNA Sequence
    7. Unit 2.7 The InterPro Database and Tools for Protein Domain Analysis
    8. Unit 2.8 Using the Gibbs Motif Sampler to Find Conserved Domains in DNA and Protein Sequences
    9. Unit 2.9 Using CorePromoter to Find Human Core Promoters
    10. Unit 2.10 Using the Structure-Function Linkage Database to Characterize Functional Domains in Enzymes
    11. Unit 2.11 Using Weeder for the Discovery of Conserved Transcription Factor Binding Sites
    12. Unit 2.12 Using PhyloCon to Identify Conserved Regulatory Motifs
    13. Unit 2.13 Using CisGenome to Analyze ChIP-chip and ChIP-seq Data
    14. Unit 2.14 Using MACS to Identify Peaks from ChIP-Seq Data
  5. Chapter 3 Finding Similarities and Inferring Homologies
    1. Unit 3.1 An Introduction to Sequence Similarity (“Homology”) Searching
    2. Unit 3.2 Finding Homologs to Nucleic Acid or Protein Sequences Using the Framesearch Program
    3. Unit 3.3 Finding Similar Nucleotide Sequences Using Network BLAST Searches
    4. Unit 3.4 Finding Homologs in Amino Acid Sequences Using Network BLAST Searches
    5. Unit 3.5 Selecting the Right Protein-Scoring Matrix
    6. Unit 3.6 Constructing and Refining Multiple Sequence Alignments with PileUp, SeqLab, and the GCG Suite
    7. Unit 3.7 An Overview of Multiple Sequence Alignment
    8. Unit 3.8 Computing Multiple Sequence/Structure Alignments with the T-Coffee Package
    9. Unit 3.9 Finding Protein and Nucleotide Similarities with FASTA
    10. Unit 3.10 Mathematically Complete Nucleotide and Protein Sequence Searching Using Ssearch
    11. Unit 3.11 Installing, Maintaining, and Using a Local Copy of BLAST for Intranet and Workstation Use
  6. Chapter 4 Annotating Genes
    1. Unit 4.1 An Overview of Gene Identification: Approaches, Strategies, and Considerations
    2. Unit 4.2 Using MZEF to Find Internal Coding Exons
    3. Unit 4.3 Using geneid to Identify Genes
    4. Unit 4.4 Using GlimmerM to Find Genes in Eukaryotic Genomes
    5. Unit 4.5 Gene Identification in Prokaryotic Genomes, Phages, Metagenomes, and EST Sequences with GeneMarkS Suite
    6. Unit 4.6 Eukaryotic Gene Prediction Using GeneMark.hmm-E and GeneMark-ES
    7. Unit 4.7 Application of FirstEF to Find Promoters and First Exons in the Human Genome
    8. Unit 4.8 Using N-SCAN or TWINSCAN to Predict Gene Structures in Genomic DNA Sequences
    9. Unit 4.9 GrailEXP and Genome Analysis Pipeline for Genome Annotation
    10. Unit 4.10 Using RepeatMasker to Identify Repetitive Elements in Genomic Sequences
  7. Chapter 5 Modeling Structure from Sequence
    1. Unit 5.1 An Introduction to Modeling Structure from Sequence
    2. Unit 5.2 FAMS and FAMSBASE for Protein Structure
    3. Unit 5.3 Modeling Membrane Proteins Utilizing Information from Silent Amino Acid Substitutions
    4. Unit 5.4 Representing Structural Information with RasMol
    5. Unit 5.5 Using Dali for Structural Comparison of Proteins
    6. Unit 5.6 Comparative Protein Structure Modeling Using Modeller
    7. Unit 5.7 Using VMD: An Introductory Tutorial
  8. Chapter 6 Inferring Evolutionary Relationships
    1. Unit 6.1 Introduction to Inferring Evolutionary Relationships
    2. Unit 6.2 Visualizing Phylogenetic Trees Using TreeView
    3. Unit 6.3 Getting a Tree Fast: Neighbor Joining, FastME, and Distance-Based Methods
    4. Unit 6.4 Inferring Evolutionary Trees with PAUP*
    5. Unit 6.5 Using MODELTEST and PAUP* to Select a Model of Nucleotide Substitution
    6. Unit 6.6 Maximum-Likelihood Analysis Using TREE-PUZZLE
    7. Unit 6.7 What If I Don't Have a Tree?: Split Decomposition and Related Models
    8. Unit 6.8 Using PEBBLE for the Evolutionary Analysis of Serially Sampled Molecular Sequences
    9. Unit 6.9 Phylogenomic Inference of Protein Molecular Function
    10. Unit 6.10 Using OrthoCluster for the Detection of Synteny Blocks Among Multiple Genomes
    11. Unit 6.11 Inferring Protein Function from Homology Using the Princeton Protein Orthology Database (P-POD)
    12. Unit 6.12 Using OrthoMCL to Assign Proteins to OrthoMCL-DB Groups or to Cluster Proteomes Into New Ortholog Groups
  9. Chapter 7 Analyzing Expression Patterns
    1. Unit 7.1 Analysis of Expression Data: An Overview
    2. Unit 7.2 The Gene Ontology (GO) Project: Structured Vocabularies for Molecular Biology and Their Application to Genome and Expression Analysis
    3. Unit 7.3 Analysis of Gene-Expression Data Using J-Express
    4. Unit 7.4 DRAGON and DRAGON View: Information Annotation and Visualization Tools for Large-Scale Expression Data
    5. Unit 7.5 Using GenMAPP and MAPPFinder to View Microarray Data on Biological Pathways and Identify Global Trends in the Data
    6. Unit 7.6 Pathway-Based Analysis of Microarray and RNAseq Data Using Pathway Processor 2.0
    7. Unit 7.7 An Overview of Spotfire for Gene-Expression Studies
    8. Unit 7.8 Loading and Preparing Data for Analysis in Spotfire
    9. Unit 7.9 Analyzing and Visualizing Expression Data with Spotfire
    10. Unit 7.10 Microarray Data Visualization and Analysis with the Longhorn Array Database (LAD)
    11. Unit 7.11 Gene Expression Analysis via Multidimensional Scaling
    12. Unit 7.12 Using GenePattern for Gene Expression Analysis
    13. Unit 7.13 Data Storage and Analysis in ArrayExpress and Expression Profiler
    14. Unit 7.14 Analyzing Gene Expression Data from Microarray and Next-Generation DNA Sequencing Transcriptome Profiling Assays Using GeneSifter Analysis Edition
  10. Chapter 8 Analyzing Molecular Interactions
    1. Unit 8.1 Analyzing Molecular Interactions
    2. Unit 8.2 Prediction of Protein-Protein Interaction Networks
    3. Unit 8.3 Evaluation of Electrostatic Interactions
    4. Unit 8.4 Using DelPhi to Compute Electrostatic Potentials and Assess Their Contribution to Interactions
    5. Unit 8.5 Searching the MINT Database for Protein Interaction Information
    6. Unit 8.6 Identifying Functional Sites Based on Prediction of Charged Group Behavior
    7. Unit 8.7 Using the Reactome Database
    8. Unit 8.8 Analyzing Networks with VisANT
    9. Unit 8.9 Searching, Viewing, and Visualizing Data in the Biomolecular Interaction Network Database (BIND)
    10. Unit 8.10 Active Site Profiling to Identify Protein Functional Sites in Sequences and Structures Using the Deacon Active Site Profiler (DASP)
    11. Unit 8.11 Structure-Based pKa Calculations Using Continuum Electrostatics Methods
    12. Unit 8.12 Flexible Ligand Docking with Glide
    13. Unit 8.13 Exploring Biological Networks with Cytoscape Software
    14. Unit 8.14 Using AutoDock for Ligand-Receptor Docking
    15. Unit 8.15 Analyzing Protein-Protein Interactions from Affinity Purification-Mass Spectrometry Data with SAINT
    16. Unit 8.16 Using ProHits to Store, Annotate, and Analyze Affinity Purification–Mass Spectrometry (AP-MS) Data
    17. Unit 8.17 Using MEMo to Discover Mutual Exclusivity Modules in Cancer
  11. Chapter 9 Building Biological Databases
    1. Unit 9.1 Creating Databases for Biological Information: An Introduction
    2. Unit 9.2 Structured Query Language (SQL) Fundamentals
    3. Unit 9.3 Modeling Biology Using Relational Databases
    4. Unit 9.4 Using Relational Databases for Improved Sequence Similarity Searching and Large-Scale Genomic Analyses
    5. Unit 9.5 Using Apollo to Browse and Edit Genome Annotations
    6. Unit 9.6 Using Chado to Store Genome Annotation Data
    7. Unit 9.7 PubSearch and PubFetch: A Simple Management System for Semiautomated Retrieval and Annotation of Biological Information from the Literature
    8. Unit 9.8 Installing and Configuring CMap
    9. Unit 9.9 Using the Generic Genome Browser (GBrowse)
    10. Unit 9.10 Installing a Local Copy of the Reactome Web Site and Database
    11. Unit 9.11 Browsing Multidimensional Molecular Networks with the Generic Network Browser (N-Browse)
    12. Unit 9.12 Using the Generic Synteny Browser (GBrowse_syn)
    13. Unit 9.13 Setting Up the JBrowse Genome Browser
    14. Unit 9.14 Administering GBrowse Sites with WebGBrowse
  12. Chapter 10 Comparing Genomes
    1. Unit 10.1 Introduction to Comparing Large Sequence Sets
    2. Unit 10.2 PipMaker: A World Wide Web Server for Genomic Sequence Alignments
    3. Unit 10.3 Using MUMmer to Identify Similar Regions in Large Sequence Sets
    4. Unit 10.4 MultiPipMaker: A Comparative Alignment Server for Multiple DNA Sequences
    5. Unit 10.5 Using Galaxy to Perform Large-Scale Interactive Data Analyses
    6. Unit 10.6 Obtaining Comparative Genomic Data with the VISTA Family of Computational Tools
    7. Unit 10.7 Using QIIME to Analyze 16S rRNA Gene Sequences from Microbial Communities
    8. Unit 10.8 Using BLAT to Find Sequence Similarity in Closely Related Genomes
    9. Unit 10.9 The Bluejay Genome Browser
    10. Unit 10.10 Using the Wash U Epigenome Browser to Examine Genome-Wide Sequencing Data
  13. Chapter 11 Assembling and Mapping Large Sequence Sets
    1. Unit 11.1 An Introduction to the Informatics of “Next-Generation” Sequencing
    2. Unit 11.2 Viewing and Editing Assembled Sequences Using Consed
    3. Unit 11.3 Generating a Genome Assembly with PCAP
    4. Unit 11.4 Assembling Genomic DNA Sequences with PHRAP
    5. Unit 11.5 Using the Velvet de novo Assembler for Short-Read Sequencing Technologies
    6. Unit 11.6 RNA-Seq Read Alignments with PALMapper
    7. Unit 11.7 Aligning Short Sequencing Reads with Bowtie
    8. Unit 11.8 Next Generation Sequence Assembly with AMOS
    9. Unit 11.9 Using Cloud Computing Infrastructure with CloudBioLinux, CloudMan, and Galaxy
  14. Chapter 12 Analyzing RNA Sequence and Structure
    1. Unit 12.1 An Overview of RNA Structure Prediction and Applications to RNA Gene Prediction and RNAi Design
    2. Unit 12.2 RNA Secondary Structure Analysis Using the Vienna RNA Package
    3. Unit 12.3 RNAi: Design and Analysis
    4. Unit 12.4 Predicting the Secondary Structure Common to Two RNA Sequences with Dynalign
    5. Unit 12.5 Annotating Non-Coding RNAs with Rfam
    6. Unit 12.6 RNA Secondary Structure Analysis Using RNAstructure
    7. Unit 12.7 Identifying Structural Noncoding RNAs Using RNAz
    8. Unit 12.8 RNA Secondary Structure Analysis Using The RNAshapes Package
    9. Unit 12.9 miRBase: microRNA Sequences and Annotation
    10. Unit 12.10 Identification of Novel and Known miRNAs in Deep-Sequencing Data with miRDeep2
    11. Unit 12.11 Comparative ncRNA Gene and Structure Prediction Using Foldalign and FoldalignM
  15. Chapter 13 Using Proteomics Techniques
    1. Unit 13.1 Proteomics and the Analysis of Proteomic Data: An Overview of Current Protein-Profiling Technologies
    2. Unit 13.2 Finding Protein Sequences Using PROWL
    3. Unit 13.3 Protein Identification Using Sorcerer 2 and SEQUEST
    4. Unit 13.4 Validation of Tandem Mass Spectrometry Database Search Results Using DTASelect
    5. Unit 13.5 Installation and Use of LabKey Server for Proteomics
    6. Unit 13.6 Using ProSight PTM and Related Tools for Targeted Protein Identification and Characterization with High Mass Accuracy Tandem MS Data
    7. Unit 13.7 Using BiblioSpec for Creating and Searching Tandem MS Peptide Libraries
    8. Unit 13.8 Using the Proteomics Identifications Database (PRIDE)
    9. Unit 13.9 Using GFS to Identify Encoding Genomic Loci from Protein Mass Spectral Data
    10. Unit 13.10 De Novo Interpretation of Tandem Mass Spectra
    11. Unit 13.11 Extracting Biological Meaning from Large Gene Lists with DAVID
    12. Unit 13.12 Census for Proteome Quantification
    13. Unit 13.13 Analyzing Shotgun Proteomic Data with PatternLab for Proteomics
    14. Unit 13.14 Predicting Peptide Retention Times for Proteomics
    15. Unit 13.15 Biological Sequence Motif Discovery Using motif-x
    16. Unit 13.16 Using the scan-x Web Site to Predict Protein Post-Translational Modifications
    17. Unit 13.17 Identifying Proteomic LC-MS/MS Data Sets with Bumbershoot and IDPicker
    18. Unit 13.18 Identification of Peptide Features in Precursor Spectra Using Hardklör and Krönik
    19. Unit 13.19 PatternLab: From Mass Spectra to Label-Free Differential Shotgun Proteomics
    20. Unit 13.20 Byonic: Advanced Peptide and Protein Identification Software
    21. Unit 13.21 Proteomics and the Analysis of Proteomic Data: 2013 Overview of Current Protein-Profiling Technologies
  16. Chapter 14 Cheminformatics and Metabolomics
    1. Unit 14.1 Introduction to Cheminformatics
    2. Unit 14.2 Using Pharmabase to Perform Pharmacological Analyses of Cell Function
    3. Unit 14.3 Using MSDchem to Search the PDB Ligand Dictionary
    4. Unit 14.4 In Silico Drug Exploration and Discovery Using DrugBank
    5. Unit 14.5 Using ChemBank to Probe Chemical Biology
    6. Unit 14.6 Using ZINC to Acquire a Virtual Screening Library
    7. Unit 14.7 PharmGKB: An Integrated Resource of Pharmacogenomic Data and Knowledge
    8. Unit 14.8 Exploring Human Metabolites Using the Human Metabolome Database
    9. Unit 14.9 ChEBI: An Open Bioinformatics and Cheminformatics Resource
    10. Unit 14.10 Metabolomic Data Processing, Analysis, and Interpretation Using MetaboAnalyst
    11. Unit 14.11 LC-MS Data Processing with MAVEN: A Metabolomic Analysis and Visualization Engine
  17. Chapter 15 Understanding Genome Variation
    1. Unit 15.2 Some Phenotype Association Tools in Galaxy: Looking for Disease SNPs in a Full Genome
    2. Unit 15.3 Genotyping in the Cloud with Crossbow
  18. Appendix 1 User Fundamentals
    1. 1A IUPAC/IUB Single-Letter Codes Within Nucleic Acid and Amino Acid Sequences
    2. 1B Common File Formats
    3. 1C Unix Survival Guide
    4. 1D X Window System Survival Guide
    5. 1E Sequence File Format Conversion with Command-Line Readseq
  19. Appendix 2 Glossary of Bioinformatics Terms
    1. 2 Glossary of Bioinformatics Terms
  20. Appendix 3 Fundamentals of Bioinformatics
    1. 3A An Introduction to Hidden Markov Models

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