Bioinformatics
Kaup valmöguleikar
Umsagnir um þriðju útgáfu Bioinformatics: „Þessa bók er einstaklega ánægjulegt að lesa og nota í starfi.“ — Briefings in Bioinformatics
„Þetta rit hefur ótvírætt og sérstakt gildi, enda býður það upp á einstaka nákvæmni og sérfræðiþekkingu fremstu lífupplýsingafræðinga, þar á meðal höfunda vinsælla verkfæra á sviðinu.“ — ChemBioChem
„Verðmæt yfirsýn yfir þetta heillandi fræðasvið. Mér fannst þetta gagnlegasta bókin um lífupplýsingafræði sem ég hef séð og mæli eindregið með henni.“ — American Society for Microbiology News
„Þessi bók ætti að vera í bókahillu sérhvers sameindalíffræðings.“ — The Quarterly Review of Biology
Lífupplýsingafræði fleygir fram. Með þróun nýrra greiningaraðferða, sem nýta nýjustu framfarir í vélanámi og gagnavísindum, öðlast líffræðingar nú áður óþekkta innsýn í flóknustu kerfi náttúrunnar.
Erfitt getur þó verið að fylgjast með þessum hröðu nýjungum. Í aukinni fjórðu útgáfu metsölubókarinnar Bioinformatics er brugðist við því með heildstæðu yfirliti yfir stöðu fræðasviðsins fyrir nemendur og fagfólk. Bókin hefur verið endurskoðuð með hliðsjón af nýlegum framförum í reiknilíffræði og veitir hagnýta leiðsögn um söfnun, greiningu og túlkun gagna. Einnig er fjallað um öflugustu reikniritin sem nú eru notuð við líffræðilegar rannsóknir og uppgötvanir.
Bioinformatics, Fourth Edition er aðgengileg, ítarleg og uppfærð inngangsbók fyrir líffræðinga á öllum náms- og starfsstigum. Hún fjallar bæði um grundvallarhugtök sem hafa staðist tímans tönn og mikilvægar nýjungar sem knýja þessa ört vaxandi fræðigrein áfram. Í nýju útgáfunni er meðal annars að finna:
- Nýja kafla um efnaskiptamengjafræði, stofnerfðafræði, metagenomics, greiningu örverusamfélaga og yfirfærslulífupplýsingafræði.
- Ítarlega umfjöllun um beitingu tölfræðilegra aðferða á líffræðileg gögn.
- Sérstaka efnisramma og viðauka þar sem rannsóknaraðferðir og flókin hugtök eru útskýrð.
- Skýrðar heimildaskrár, ítarlega lista yfir viðeigandi vefheimildir og umfangsmikinn orðalista yfir algeng hugtök í lífupplýsingafræði, erfðamengjafræði og prótínmengjafræði.
Bioinformatics er ómissandi handbók fyrir rannsakendur og nemendur á öllum stigum í sameindalíffræði og reiknilíffræði, sem og fyrir þá sem starfa við erfðamengjarannsóknir, klínískar rannsóknir, prótínmengjafræði og skyld fræðasvið.
Praise for the third edition of Bioinformatics “This book is a gem to read and use in practice. ” --Briefings in Bioinformatics "This volume has a distinctive, special value as it offers an unrivalled level of details and unique expert insights from the leading computational biologists, including the very creators of popular bioinformatics tools. " --ChemBioChem “A valuable survey of this fascinating field.
. . I found it to be the most useful book on bioinformatics that I have seen and recommend it very highly. ” --American Society for Microbiology News “This should be on the bookshelf of every molecular biologist. ” --The Quarterly Review of Biology The field of bioinformatics is advancing at a remarkable rate. With the development of new analytical techniques that make use of the latest advances in machine learning and data science, today’s biologists are gaining fantastic new insights into the natural world’s most complex systems.
These rapidly progressing innovations can, however, be difficult to keep pace with. The expanded fourth edition of the best-selling Bioinformatics aims to remedy this by providing students and professionals alike with a comprehensive survey of the current field. Revised to reflect recent advances in computational biology, it offers practical instruction on the gathering, analysis, and interpretation of data, as well as explanations of the most powerful algorithms presently used for biological discovery.
Bioinformatics, Fourth Edition offers the most readable, up-to-date, and thorough introduction to the field for biologists at all levels, covering both key concepts that have stood the test of time and the new and important developments driving this fast-moving discipline forwards. This new edition features: New chapters on metabolomics, population genetics, metagenomics and microbial community analysis, and translational bioinformatics A thorough treatment of statistical methods as applied to biological data Special topic boxes and appendices highlighting experimental strategies and advanced concepts Annotated reference lists, comprehensive lists of relevant web resources, and an extensive glossary of commonly used terms in bioinformatics, genomics, and proteomics Bioinformatics is an indispensable companion for researchers, instructors, and students of all levels in molecular biology and computational biology, as well as investigators involved in genomics, clinical research, proteomics, and related fields.
Nánar um bókina
- Wiley Global Research (STMS)
- 9781119335955
- 9781119335580
- ePub
- 4
- Andreas D. Baxevanis; Gary D. Bader; David S. Wishart
- English
- 2020-02-21
- 100
- 10
- 2
Kaflar
- Cover
- Foreword
- Preface
- Contributors
- About the Companion Website
- 1 Biological Sequence Databases
- Introduction
- Nucleotide Sequence Databases
- Nucleotide Sequence Flatfiles: A Dissection
- Protein Sequence Databases
- Summary
- Acknowledgments
- Internet Resources
- Further Reading
- References
- 2 Information Retrieval from Biological Databases
- Introduction
- Integrated Information Retrieval: The Entrez System
- Medical Databases
- Organismal Sequence Databases Beyond NCBI
- Summary
- Further Reading
- References
- 3 Assessing Pairwise Sequence Similarity: BLAST and FASTA
- Introduction
- Global Versus Local Sequence Alignments
- Scoring Matrices
- BLAST
- BLAST 2 Sequences
- MegaBLAST
- PSI-BLAST
- BLAT
- FASTA
- Summary
- Further Reading
- References
- 4 Genome Browsers
- Introduction
- The UCSC Genome Browser
- UCSC Table Browser
- ENSEMBL Genome Browser
- Ensembl Biomart
- JBrowse
- Summary
- Further Reading
- References
- 5 Genome Annotation
- Introduction
- Gene Prediction Methods
- Ab Initio Gene Prediction in Prokaryotic Genomes
- Ab Initio Gene Prediction in Eukaryotic Genomes
- How Well Do Gene Predictors Work?
- Assessing Prokaryotic Gene Predictors
- Assessing Eukaryotic Gene Predictors
- Evidence Generation for Genome Annotation
- Gene Annotation and Evidence Generation using Comparative Gene Prediction
- Genome Annotation Pipelines
- Summary
- Acknowledgments
- Internet Resources
- Further Reading
- References
- 6 Predictive Methods Using RNA Sequences
- Introduction
- Overview of RNA Secondary Structure Prediction Using Thermodynamics
- Dynamic Programming
- Accuracy of RNA Secondary Structure Prediction
- Predicting the Secondary Structure Common to Multiple RNA Sequences
- Practical Introduction to Single-Sequence Methods
- Practical Introduction to Multiple Sequence Methods
- Other Computational Methods to Study RNA Structure
- Comparison of Methods
- Predicting RNA Tertiary Structure
- Summary
- Further Reading
- References
- 7 Predictive Methods Using Protein Sequences
- Introduction
- One-Dimensional Prediction of Protein Structure
- Predicting Protein Function
- Summary
- Further Reading
- References
- 8 Multiple Sequence Alignments
- Introduction
- Measuring Multiple Alignment Quality
- Making an Alignment: Practical Issues
- Commonly Used Alignment Packages
- Viewing a Multiple Alignment
- Summary
- References
- 9 Molecular Evolution and Phylogenetic Analysis
- Introduction
- Early Classification Schemes
- Sequences As Molecular Clocks
- Background Terminology and the Basics
- How to Construct a Tree
- Marker-Based Evolution Studies
- Phylogenetic Analysis and Data Integration
- Future Challenges
- References
- 10 Expression Analysis
- Introduction
- Step 0: Choose an Expression Analysis Technology
- Step 1: Design the Experiment
- Step 2: Collect and Manage the Data – and Metadata
- Step 3: Data Pre-Processing
- Step 4: Quality Control
- Step 5: Normalization and Batch Effects
- Step 6: Exploratory Data Analysis
- Step 7: Differential Expression Analysis
- Step 8: Exploring Mechanisms Through Functional Enrichment Analysis
- Step 9: Developing a Classifier
- Single-Cell Sequencing
- Summary
- Further Reading
- References
- 11 Proteomics and Protein Identification by Mass Spectrometry
- Introduction
- Mass Spectrometry
- Tandem Mass Spectrometry for Peptide Identification
- Sample Preparation
- Bioinformatics Analysis for MS-based Proteomics
- Proteomics Strategies
- Peptide Mass Fingerprinting
- PMF on the Web
- Proteomics and Tandem MS
- PSM Software
- PSM on the Web
- Reporting Standards
- Proteomics Data Repositories
- Protein/Proteomics Databases
- Selected Applications of Proteomics
- Summary
- Acknowledgments
- Internet Resources
- Further Reading
- References
- 12 Protein Structure Prediction and Analysis
- Introduction to Protein Structures
- How Protein Structures are Determined
- How Protein Structures are Described
- Protein Structure Databases
- Visualizing Proteins
- Protein Structure Prediction
- Protein Structure Evaluation
- Protein Structure Comparison
- Summary
- Further Reading
- References
- 13 Biological Networks and Pathways
- Introduction
- Pathway and Molecular Interaction Mapping: Experiments and Predictions
- Pathway and Molecular Interaction Databases: An Overview
- Pathway Databases
- Molecular Interaction Databases
- Functional Interaction Databases
- Strategies for Navigating Pathway and Interaction Databases
- Standard Data Formats for Pathways and Molecular Interactions
- Pathway Visualization and Analysis
- Network Visualization and Analysis
- Summary
- Acknowledgments
- Internet Resources
- Further Reading
- References
- 14 Metabolomics
- Introduction
- Data Formats
- Databases
- Bioinformatics for Metabolite Identification
- Multivariate Statistics
- Bioinformatics for Metabolite Interpretation
- Summary
- Further Reading
- References
- 15 Population Genetics
- Introduction
- Evolutionary Processes and Genetic Variation
- Allele Frequencies and Population Variation
- Display Methods
- Demographic History Inference
- Admixture and Ancestry Estimation
- Detection of Natural Selection
- Other Applications
- Summary
- References
- 16 Metagenomics and Microbial Community Analysis
- Introduction
- Why Study the Microbiome?
- The Origins of Microbiome Analysis
- Metagenomic Workflow
- General Considerations in Marker-Gene and Metagenomic Data Analysis
- Marker Genes
- Metagenomic Data Analysis
- Other Techniques to Characterize the Microbiome
- Summary
- Further Reading
- References
- 17 Translational Bioinformatics
- Introduction
- Databases Describing the Genetics of Human Health
- Prediction and Characterization of Impactful Genetic Variants from Sequence
- Computing with Patient Phenotype Using Data in Electronic Health Records
- Informatics and Precision Medicine
- Ethical, Legal, and Social Implications of Translational Medicine
- Summary
- References
- 18 Statistical Methods for Biologists
- Introduction
- Descriptive Representations of Data
- Statistical Inference and Statistical Hypothesis Testing
- Summary
- Acknowledgments
- Internet Resources
- Further Reading
- References
- Appendices
- 1.1 Example of a Flatfile Header in ENA Format
- 1.2 Example of a Flatfile Header in DDBJ/GenBank Format
- 1.3 Example of a Feature Table in ENA Format
- 1.4 Example of a Feature Table in GenBank/DDBJ Format
- 6.1 Dynamic Programming
- Reference
- Glossary
- Index
- End User License Agreement