About Course
Description
This book, Bioinformatics: Volume I – Data, Sequence Analysis, and Evolution, is part of the Methods in Molecular Biology series and provides a comprehensive guide to bioinformatics methodologies. It focuses on data handling, sequence analysis, and evolutionary studies, offering practical protocols and tools for researchers. The second edition includes updated content and online resources, making it an essential resource for anyone working in computational biology and genomics.
Implementation Plan for the Book Club Over Two Months
1. Book Selection
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Book: Bioinformatics: Volume I – Data, Sequence Analysis, and Evolution.
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Level: Intermediate to Advanced.
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Total Chapters: 14 (approximate).
2. Chapter Division
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The book will be divided into 8 parts (one part per week).
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Each week, members will read 1-2 chapters depending on the length and complexity.
3. Weekly Schedule
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Week 1: Chapter 1 (Introduction to Bioinformatics) + Chapter 2 (Data Management in Bioinformatics).
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Week 2: Chapter 3 (Sequence Alignment Techniques) + Chapter 4 (Advanced Sequence Analysis).
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Week 3: Chapter 5 (Genome Annotation) + Chapter 6 (Genome Analysis Tools).
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Week 4: Chapter 7 (Introduction to Phylogenetics) + Chapter 8 (Phylogenetic Tree Construction).
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Week 5: Chapter 9 (Molecular Evolution) + Chapter 10 (Evolutionary Models).
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Week 6: Chapter 11 (Applications of Evolutionary Biology) + Chapter 12 (Computational Tools for Evolution).
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Week 7: Chapter 13 (Case Studies in Bioinformatics) + Chapter 14 (Future Directions in Bioinformatics).
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Week 8: Review and Final Discussion (Recap of Key Concepts and Takeaways).
4. Weekly Meetings
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Duration: 1-2 hours per meeting.
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Agenda:
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Discuss the assigned chapters.
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Explain complex concepts with the help of an instructor.
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Answer members’ questions.
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Open discussion on ideas presented in the chapters.
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Use interactive tools like presentations or videos to enhance understanding.
5. Interactive Activities
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Workshops: Organize practical workshops on using bioinformatics tools (e.g., sequence alignment software, phylogenetic tree builders).
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Side Discussions: Create a Facebook or WhatsApp group for discussions outside meetings.
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Weekly Challenges: For example, writing a summary of the week’s chapters or analyzing a small dataset.
6. Final Evaluation
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At the end of the two months, conduct a final evaluation:
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Survey to assess the reading and meeting experience.
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General discussion session about the book as a whole.
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Members share their personal evaluation of the book and what they learned.
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What Will You Learn?
- Data management and preprocessing in bioinformatics.
- Sequence alignment and comparison techniques.
- Genome and protein sequence analysis.
- Evolutionary biology and phylogenetic analysis.
- Computational tools and algorithms for biological data.
- Practical protocols and step-by-step methodologies.
Course Content
Before You Start: Book Club Orientation
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bioinformatics
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Bioinformatics
chapter 1.
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Abstract
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1 Introduction
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1 1 General Procedure for Genome Sequencing
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1 2 Choosing a Sequencing Strategy
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2 Materials
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3 Methods
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3 1 First Generation Technologies
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3 2 TheBirthofNext Generation SequencingNGS
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3 3 Second Generation Sequencing
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3 3 2 The Illumina Solexa Genome Analyzer
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3 3 3 Applied Biosystems SOLiD Sequencer
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3 3 4 Polonator
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3 3 5 Shortcomings of Second Generation DNA
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3 4 Third Generation Sequencing
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3 4 2 DNA Nanoball Sequencing
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3 4 3 Pacific Bioscience RS SMRT Sequencing
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3 4 4 Nanopore Sequencing
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4 Applications of Sequencing
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5 Future Aspects
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6 Notes
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Chapter 2
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Abstract
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1 Introduction
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2 Materials
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3 Methods
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3. 2 Using PCAP
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END OF Ch 2 Sequence Assembly3 3 Troubleshooting
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Chapter 3
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Abstract
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1 .1 Introduction Protein Crystallization
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1. 2 Crystal Preparation and Data Collection
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1. 3 Structure Determination
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1 .4 Structure Refinement
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2 Materials 2 1 Crystallization and Crystal Preparation
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3 Methods 3 1 Crystallization and Crystal Preparation
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3 .2 Data Measurement
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3. 3 Data Processing 3 3 1 HKL2000
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3. 4 Molecular Replacement
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3 .5 The SRA Run
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3. 6 Model Building
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4 Notes
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Chapter 4
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Abstract
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1 Structure and History of Sequence Databases at NCBI
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1. 1 INSDC
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1. 2 SRAGEO
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1. 3 Bioproject
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1. 4 BioSample
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1 .5 GenBank
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1 .6 Genomes
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1. 7 Metagenomes and Environmental Sample Sequencing
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1 .8 The GenBank Sequence Record
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1 .9 Updates and Maintenance of the Database
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1. 10 Pitfalls of an Archival Primary
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1. 1.1 RefSeq
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2 Submission of Sequence Data to NCBI Archives
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2. 1 SRA Submissions
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2. 2 GenBank Submissions
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3 Finding Sequence Data in SRA and GenBank
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3 .5 The SRA Run Selector
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3. 6 BioProject Browsing Linking
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3. 7 BioProject Query
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3. 8 BioProject Linking
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3. 9 GenBank
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3 .10 Genomes
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4 Downloading the Sequence Data in SRA
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5 Conclusion
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Chapter 5
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Abstract
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1 Introduction
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Materials 2 1
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2. 1. 2 Epigenetic Modifications and Chromati
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2. 1. 3 Evolutionary Conservation and Variation
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2 1 4 Collaboration Genome Annotation
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2. 2 Technical Frameworks to Use Genome
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2. 2. 2 Genome Browsers
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2. 2. 3 Further Use of Genome Annotation
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3 Methods 3 1 Scenario I Search
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3 .2 Scenario II Make and Browse Your Own
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4 Notes
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Chapter 6
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Abstract
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1 Introduction
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1 .1 Theoretical Background
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1 .2 Applications
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2 Materials
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2 .1 Finding and Accessing Ontologies
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2. 2 Encoding Ontologies
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2. 3 Editing Ontologies
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3 Methods 3
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3. 2 Biological Pathway Exchange Ontology
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4 Notes
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.Chapter 7
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Abstract
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1. Introduction
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2 What is a Protein Domain
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3 Classification of Domains from Sequence
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3 1 Automatic Domain Sequence Clustering
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3. 2 Whole Chain
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3 .3 Families Represented by Multiple Sequence Alignments
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3. 4 Domain Sequence Classifications
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3. 5 Protein Sequence Classification
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4 Classification of Domains from Structure
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4 .1 Identification of Domain Boundaries at the Structural Level
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4. 2 Methods for Structural Comparison
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4 .3 Domain Structure Classification Hierarchies
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4 .4 Structural Domain Classifications
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4 .5 Multiple Structural Alignments of Protein Domains
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4 .6 Consistency of Structure Domain Databases
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5 Domain Family Annotation of Genomes
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6 Conclusions
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7 Not
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.Chapter 8
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Abstract
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1 Introduction
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1. 2 Reliability and Evolutionary Hypothesis
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1 .3 Dynamic Programming
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1. 4 The Progressive Alignment Protocol
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1. 5 Alignment Iteration
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2 Materials 2
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2 .2 Unequal Sequence Lengths
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2. 3 Type of Alignment
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3 Methods 3
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. 3 2 MUSCLE
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3. 3 T Coffee
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3. 4 MAFFT
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3. 5 ProbCons Multiple Sequence Alignment 3
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3. 6 Kalign
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3. 7 MSAProbs
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2 Materials 2
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3. 8 Clustal Omega
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4 Notes
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.Chapter 9
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Abstract
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1 Introduction 1. 1 Homology, Similarity, and Identity
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1. 2 Substitutions and Indels
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2 Materials 2
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2. 2 Pairwise Alignment and Scoring Matrices
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2. 3 GlobalandLocal Alignment
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3 Methods 3
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3. 2 FASTA
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3. 3 Methods and Tools for Large Scale Sequence Comparison
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4 Notes
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.Chapter 10
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Abstract
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1 Introduction
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2 Reference Genomes and Genes 2
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2. 2 Reference Gene Sets
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3 Genomic Databases, and Approaches
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4 Genomic Databases, and Genome Browser Based Searches
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4. 2 Ensembl 4 2
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4. 2 Ensembl 4 2
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4 .3 Vega
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4. 4 University of California Santa Cruz UCSC Genome Browser
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4 .5 NCBI Genome, Map Viewer and Gene
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4. 6 Viral Genomes
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4. 7 Stand Alone Genome Browsers
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5 Genomic Database Searching with RNA Identifiers
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6 Genome Searching Using Karyotype Bands
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7 Genome Searching Using Chromosomal Coordinates
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8 Sequence, Motif and Matrix Based Genome Searching
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9 Performing Multiple Genomic Database Searches
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9 2 Creating an Annotated ID Table
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9. 3 Batch Retrieval of Sequences from Multiple Genomic Coordinates
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10 Genomic Database Searching Using NGS Data
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11 Complex Searches of Genomic Databases
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11. 2 Galaxy
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11. 3 NCBI Genome Workbench
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11. 4 Taverna
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12 Genome Searching Using Application Programming Interfa
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12. 1 Bio toolkits
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12. 2 Ensembl
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12. 3 The UCSC Genome Browser
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12 4 NCBI Genome Resources
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12. 5 Bioconductor
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13. Conclusions and Perspectives
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14 Notes
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Chapter 11
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Abstract
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1 Introduction
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2 Methods 2
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2. 2 Gene Finding in Environmental Sequence Samples
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2. 3 Gene Finding in Eukaryotes
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3 Conclusions
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4 Notes
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Chapter 12
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Abstract
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1 Introduction
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2 Change Point Analysis 2
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2. 2 The Bayesian Segmentation and Classification Model BSCM A Model for changept
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2 .3 MCMC Simulation
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3 Changept Application The GUI and a Worked Example
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3. 1 The Input Sequences
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3. 2 Running changept Using the changeptGUI
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3 .3 Model Selection
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3. 4 The Segmentation Map
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4 Notes 4
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Chapter 13
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Abstract
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2 Expected Signatures of Natural Selection
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3. Three Steps to dN dS
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3. 1 Step 1 Counting Synonymous S and Non synonymous N Sites
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3 .2 Step 2 Counting Synonymous S and Non synonymous N Differences
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3 .3 Step 3
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4 Moving Away from the Naive Model
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4. 2 The Importance of the Transition
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4 .3 Codon Frequency Model
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4 .4 Amount of Divergence
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5 Model Selection
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6 Assumptions to Keep in Mind
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7 Final Remarks
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8 Notes
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Chapter 14
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Abstract
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1 Introduction
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2 BeforeTreeInference
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2. 1 Assumptions About the Sequence Data
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2 .2 The Tree Assumption
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2. 3 Model Assumptions
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3 Scoring Trees
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3 .2 Why Estimating Trees Is Difficult
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4 Inferring Trees Using Maximum Likelihood
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4 .1 Proposing an Initial Tree
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4. 2 Refining the Tree Estimate
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4. 3 Stopping Criteria Inferring Trees
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4 .4 Resampling from Tree Space
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4 5 Other Approaches to Point Estimation
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4. 6 Choosing a Model and Partitioning Data
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5. HowGood
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5. 1 Measures of General Branch Support and Bootstrapping
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5. 2 Confidence Sets of Trees The SH and AU Test
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5. 3 Other Tests of Tree Topologies
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6 Bayesian Inference
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6. 1 Bayesian Estimation of Trees
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6. 2 Sampling the Posterior Using
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6 .3 How Long to Run a Markov Chain Monte Carlo
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6 .4 The Specification of Priors
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7 Strengths and Weaknesses of Statistical Methods
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8 Notes
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Chapter 15
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Identifying Optimal Models of Evolution Abstra
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1 Introduction
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2 Underlying Principles
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2 1 The Phylogenetic Assumptions
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2 .3 Modeling the Evolutionary
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3 Choosing a Substitution Model
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3 .3 Testing the Stationary, Reversible, and Homogeneous Condition
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3. 4 Testing the Assumption of Independent and Identical Processes
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3 5 ChoosingaTime reversible Substitution Model
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3. 6 General Approaches to Model
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4 Discussion
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Chapter 16
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Scaling Up the Phylogenetic Detection of Lateral
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1 Introduction
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2 Systems, Software, and Databases 2
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3 Methods
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3. 2 Multiple Sequence Alignment
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3 .3 Inference
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3 .4 Reference Topology
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3 .5 Inference of Lateral Transfer Events via Topological Comparisons of Trees
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4 Notes
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Chapter 17
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Abstract
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1 Introduction
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2 Program Usage 2
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2 .2 Program Settings
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2. 3 Producing a Preliminary Recombination Hypothesis
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2. 4 Making a Recombination Free Dataset
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2. 5 Navigating Through the Analysis Results
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2. 6 Checking the Accuracy of Breakpoint Identification
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2. 7 Checking the Accuracy of Recombinant Sequence Identification
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2 .8 Evaluating How Well Recombination Signals Have Been Grouped into Recombination Events
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2 .9 Accepting a Verified Recombination Event
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2 .10 Saving Analysis Results
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3 Examples
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3. 2 Navigating Through the Results
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3 .3 Checking the Accuracy of Breakpoint Identification
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3 .4 Checking the Accuracy of Recombinant Sequence Identification
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3. 5 Evaluating RDP4’s Grouping of Recombination Event
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3. 6 Completing the Analysis
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3. 7 Further Analyses
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4 Notes
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Chapter 18
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Abstract
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1 Estimation of Species Trees
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2 Bayesian Inference of Species Trees
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3 The Software guenomu
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3 .1 Guenomu Programs
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4 Input Files
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5 Running guenomu 1
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5 .1 Optimization by Simulated Annealing 2
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5 .2 Output
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6 Conclusion
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THE END ….(Species Tree Estimation from Genome Wide Data )
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