Current Protocols in Bioinformatics

Table of Contents

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

* Looking for a protocol from this title that does not appear here? You can find it on Wiley Online Library