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از ساعت 7 صبح تا 10 شب
ویرایش: [2 ed.]
نویسندگان: Henrik Christensen (editor)
سری:
ISBN (شابک) : 3031452925, 9783031452925
ناشر: Springer
سال نشر: 2023
تعداد صفحات: 262
[257]
زبان: English
فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود)
حجم فایل: 14 Mb
در صورت تبدیل فایل کتاب Introduction to Bioinformatics in Microbiology (Learning Materials in Biosciences) به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب مقدمه ای بر بیوانفورماتیک در میکروبیولوژی (مواد آموزشی در علوم زیستی) نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
This updated and extended second edition of the textbook introduces the basic concepts of bioinformatics and enhances students\' skills in the use of software and tools relevant to microbiology research. It discusses the most relevant methods for analysing data and teaches readers how to draw valid conclusions from the observations obtained. Free software and servers available on the Internet are presented in an updated version of 2023 and more advanced stand-alone software is proposed as a second option. In addition, new tools for microbial genome analysis and new flowcharts that complement the didactic elements have been added. Exercises and training questionnaires are included at the end of each chapter to facilitate learning. The book is aimed at Ph.D. students and advanced undergraduate students in microbiology, biotechnology, and (veterinary) medicine with little or basic knowledge of bioinformatics.
Preface to Second Edition Contents List of Abbreviations 1: Introduction 1.1 Basics and History of Bioinformatics 1.1.1 Bioinformatics Is Integrating Many Scientific Fields 1.1.2 Homology 1.1.3 Evolution Is Related to Sequence Diversity Caused by Mutations 1.2 The Aim, Structure, and Outline of the Book 1.3 Computers and Operating Systems Required for Bioinformatics 1.4 Computer Programs and Pipelines 1.5 Activity Further Reading Basic bioinformatics text books References 2: DNA Sequence Assembly and Annotation of Genes 2.1 DNA Sequencing 2.1.1 Sanger Sequencing 2.1.2 Massive Parallel, Short-Read Sequencing 2.1.2.1 Illumina (Sequencing by Synthesis) 2.1.3 DNA Sequencing in Metagenomic and for Single Cell Sequencing 2.1.4 Real-Time, Single Molecule Sequencing 2.1.4.1 PacBio® 2.1.4.2 Nanopore Sequencing 2.2 DNA Sequence Assembly 2.2.1 Base Calling and Trimming 2.2.2 Assembly of DNA Sequences 2.2.2.1 Assembly by Overlap Consensus Methods 2.2.2.2 Assembly by k-mer Strategy 2.2.2.3 Quality Criteria of the Final Assembled DNA Sequence 2.2.2.4 De Novo or with Reference 2.3 Closing of Genomes 2.4 DNA Sequence Formats 2.5 Annotation 2.5.1 Elements from Comparative Genomics Aiming Annotation 2.6 Activities 2.6.1 Annotation at RAST Further Reading References 3: Databases and Protein Structures 3.1 Introduction to Bioinformatics Databases 3.1.1 Data Formats Used with Bioinformatics Databases 3.2 Organization of Databases and Bioinformatics Institutions 3.3 Major Bioinformatics Databases 3.3.1 GenBank 3.3.2 The European Nucleotide Archive (ENA) 3.3.3 Swiss-Prot and UniProt 3.3.4 Genomics Databases 3.3.5 Raw Sequence Read Datasets 3.3.6 Other Databases 3.3.7 Primary and Secondary Bioinformatics Databases 3.3.8 Data Formats in Bioinformatics Databases 3.4 Accession Numbers 3.5 Protein Structure Databases and Predictions 3.5.1 Primary and Secondary Structures 3.5.2 Domain Prediction and Databases 3.5.2.1 Single Motif 3.5.2.2 Multiple Motifs 3.5.2.3 Full Domain 3.5.2.4 Mixing Different Methods 3.5.3 Protein 3D Structure 3.6 Overview of Proteomics Databases and Servers 3.7 Help to Databases 3.8 Activities 3.8.1 Download a Sequence from NCBI 3.8.2 Download a Genome from NCBI 3.8.3 Deposition of Sequence with GenBank 3.8.3.1 Procedure for Single DNA Sequences 3.8.3.2 Genomic Sequence 3.8.4 Protein Structure Prediction with Swiss Model and SPDBV 3.9 Example Illustrating Variable Information and Redundancy of a Primary Genomic Database and Comparison to Some Other Information in the Book References 4: Pairwise Alignment, Multiple Alignment, and BLAST 4.1 The Pairwise Alignment Problem 4.1.1 Global or Local Pairwise Alignments? 4.1.2 Substitution Matrices 4.1.2.1 Amino Acid Substitution Matrices 4.1.2.2 Nucleotide Substitution Matrices 4.1.3 Gaps 4.1.4 Dynamic Programming 4.1.4.1 Needleman and Wunsch 4.1.4.2 Smith and Waterman 4.2 Multiple Alignment 4.2.1 Clustal 4.2.2 Other Multiple Alignment Programs 4.3 BLAST 4.3.1 NCBI BLAST 4.3.2 Ortholog Detection 4.3.3 BLAST2 sequences 4.3.4 Statistics 4.3.5 Variants of BLAST 4.4 Activities 4.4.1 Pairwise Alignment 4.4.2 Multiple Alignment with ClustalX 4.4.3 BLAST References 5: Primer Design 5.1 Background for Oligonucleotide Design 5.1.1 Practical Approach to Oligonucleotide Design Whether of Exploratory Nature or for Diagnostic Purpose 5.1.1.1 Exploratory Applications 5.1.1.2 Diagnostics Applications 5.2 General Rules for Design of Oligonucleotides 5.2.1 Lengths of PCR Primers and Products 5.2.2 Lengths of Oligonucleotide Hybridization Probes 5.3 Sequence Comparison 5.3.1 String Comparison by Score 5.3.2 Nearest Neighbor Comparisons of Duplex Stability 5.3.3 Design of Primers for PCR and “Kwok’s Rules” 5.3.4 Design of Probes for Hybridization 5.4 Tm Calculations 5.4.1 Estimation of Tm by Formula 5.4.2 Formamide Considerations 5.4.3 Estimation of Tm by Nearest Neighbor Prediction 5.5 Special Applications 5.5.1 Exploratory Applications 5.5.1.1 Degenerate Primers and Probes 5.5.1.2 Nested PCRs 5.5.2 Diagnostic Applications 5.5.2.1 Primers for Multiplex PCR 5.5.2.2 SNP Analysis 5.6 Data Formats 5.7 Programs 5.8 Activities 5.8.1 Exploratory Primers with Primer3 for Recognition of Single DNA Sequences 5.8.2 Diagnostic Primers with PrimerBLAST Further Reading Introduction to practical work with PCR as well to the historical background is found in Sambrook and Russell (2001): References 6: Introduction to Phylogenetic Analysis of Molecular Sequence Data 6.1 Background 6.2 Understanding the Phylogenetic Tree 6.3 Assumptions About Data in Order to Perform Phylogenetic Analysis 6.4 Phylogenetic Model Parameters 6.4.1 The Tree Structure 6.4.2 Substitution Matrix and Evolutionary Models 6.4.3 Weighting of Characters 6.5 Phylogenetic Methods 6.5.1 Maximum Parsimony 6.5.2 Distance Matrix/Neighbor Joining 6.5.3 Maximum Likelihood 6.5.4 Bayesian (Mr. Bayes) Inference of Phylogeny 6.6 Comparison of Phylogenetic Methods 6.6.1 Bootstrap 6.7 Whole Genome Phylogeny 6.7.1 Core Phylogeny 6.7.2 Genome Distance Phylogeny 6.8 Data Formats 6.9 Phylogenetic Program Packages 6.10 Activities 6.10.1 Neighbor Joining Phylogeny Further Reading References 7: Sequence-Based Classification and Identification 7.1 Introduction 7.2 Classification of Prokaryotes 7.2.1 Classification Based on 16S rRNA Gene Sequence Comparison 7.2.2 From DNA–DNA Hybridization of Total DNA to WGS for Classification 7.2.2.1 ANI 7.2.2.2 GGDC 7.2.3 Classification Based on Core Genome Analysis and Multilocus Sequence Analysis (MLSA) 7.3 Classification of the Taxonomic Hierarchy 7.3.1 Classification of Species 7.3.2 Classification of Genera 7.3.3 Classification of Families, Orders, Classes, and Phyla 7.4 Rules for the Naming of a New Prokaryote 7.4.1 Bacterial Species Names Are Linked to the Type Strain 7.4.1.1 Example of an Old Bacterial Name that Never Changed 7.4.1.2 Example of Taxon with Many Reclassifications and Changes in Genus Name 7.5 The Benefits of Sequence-Based Identification 7.5.1 16S rRNA Sequence-Based Identification, Step-by-Step 7.5.2 16S rRNA-Based Identification Without Culture 7.5.3 Sequence-Based Identification of Fungi 7.5.4 Sequence-Based Identification of Protists 7.6 Strain Identification by WGS Analysis 7.6.1 SNP 7.6.2 OGRI for Strain Level Conformation and Identification 7.6.3 OGRI for Fungi 7.6.4 Identification of E. coli K12 7.7 Activity 7.7.1 16S rRNA Gene Sequence-Based Identification References 8: 16S rRNA Amplicon Sequencing 8.1 Use of 16S rRNA Amplicon Sequencing, Generation of Data, and Bioinformatics Pipelines 8.1.1 Use of 16S rRNA Amplicon Sequencing and Generation of Raw Data 8.1.2 Bioinformatical Pipelines to Analyze Data 8.2 Data Analysis 8.2.1 Quality Trim by Sequence 8.2.2 Pairing of Reads 8.3 Removal of Chimeras and DNA from Other Domains or Life 8.4 Grouping of Reads into OTUs 8.5 Alignment of OTUs and Association of OTUs with Taxonomic Units 8.6 α-(Within Group) and β-Diversity (Between Groups) Comparison 8.6.1 Rarefaction Analysis 8.7 Taxonomic Comparisons 8.7.1 Generation and Interpretation of Heatmaps and Boxplots 8.8 Principal Coordinates Analysis (PCoA) 8.9 Prediction of Function 8.10 Activity QIIME2 8.10.1 Installation 8.10.2 Running QIIME2 8.10.3 Download Data 8.10.4 Change Data Format to QIIME2 Artifacts 8.10.5 Demultiplexing Sequences 8.10.6 Denoising 8.10.7 Visualization Summaries of the Data 8.10.8 Phylogenetic Tree 8.10.9 α- and β-Diversity Analyses 8.10.10 Alpha Rarefaction Plotting 8.10.11 Taxonomic Analysis 8.10.12 Exporting Data 8.10.13 Filtering Data 8.10.14 Good to Know When Working with QIIME2 8.10.14.1 Already Demultiplexed Data 8.10.14.2 Merging of Paired-End Reads 8.10.14.3 Train Your Classifier 8.10.14.4 Plugins 8.10.14.5 Decontamination References 9: Full Shotgun DNA Metagenomics 9.1 Background 9.2 Sequencing Strategies and Data Types 9.3 Analysis of Full DNA Shotgun Sequence Data 9.4 MG-RAST 9.5 Upload and Analyze on MG-RAST 9.6 Activities 9.6.1 Full DNA Metagenome–Shotgun DNA Metagenomics References 10: Transcriptomics 10.1 Introduction to Transcriptomics 10.2 Experimental Design 10.3 Preparing a RNA-seq Library 10.3.1 Step 1: Isolation of RNA 10.3.2 Step 2: Depletion or Removal of rRNA 10.3.3 Step 3: Convertion of RNA into Complementary DNA (cDNA) 10.3.4 Step 4: Addition of Sequencing Adaptors 10.3.5 Step 5: PCR Amplification (Enrichment) 10.3.6 Step 6: Quality Control of the Library 10.4 Sequencing 10.5 Data Management (Sequence Reads) 10.5.1 Raw Data 10.5.2 Alignments of Sequence Reads 10.5.3 Normalization of Data 10.6 Differential Gene Expression 10.7 Conclusion References 11: Sequenced-Based Typing and Prediction of Function 11.1 Background of Prokaryotic Populations and Population Genetics 11.1.1 Mutation 11.1.2 Selection 11.1.3 Genetic Drift 11.1.4 Migration 11.1.5 The Biological Consequences of Population Genetics of Prokaryotes 11.2 Multilocus Sequence Typing (MLST) 11.2.1 MLST 11.2.2 Multilocus Sequence Analysis 11.3 Whole Genome-Based Typing 11.3.1 Whole Genomic Multilocus Sequence Typing (wgMLST) 11.3.2 Single Nucleotide Polymorphisms (SNP) 11.3.3 Typing of Virulence, Antibiotic Resistance, and Serotype Based on the Whole Genomic Sequence 11.3.3.1 Prediction of Virulence Genes 11.3.3.2 Prediction of Antibiotic Resistance 11.3.3.3 Secondary Metabolites 11.3.3.4 Prophages 11.3.3.5 Plasmids Mobile Genetic Elements 11.3.3.6 Restriction and Modification of DNA 11.3.3.7 CRISPR 11.4 Organisms Specific Platforms for Whole Genome Sequence-Based Typing 11.5 Association of Genetic Trains with Metadata and Phylogeny 11.6 Activities 11.6.1 MLST Typing of Pasteurella multocida 11.6.2 Graphics Further Reading References Appendix Abbreviation of Amino Acids Ambiguity Table Symbols Codon Tables Index