Bioinformatics : the impact of accurate quantification on proteomic and genetic analysis and research /

The book introduces bioinformatic and statistical methodology and shows approaches to bias correction and error estimation. It also presents quantitative methods for genome and proteome analysis.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Liu, Yu (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Toronto : Apple Academic Press, 2014.
Temas:
Bioinformatics > Statistical methods.
Computational Biology > methods
Computational Biology
Data Interpretation, Statistical
Genome-Wide Association Study
Microarray Analysis
Proteome > analysis
Sequence Analysis, RNA
Bio-informatique.
Bio-informatique > Méthodes statistiques.
Étude d'association pangénomique.
NATURE > Reference.
SCIENCE > Life Sciences > Biology.
SCIENCE > Life Sciences > General.
Bioinformatics
Genetics > Research
Proteomics
Bioinformatik
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Front Cover; About the Editor; Contents; Acknowledgments and How to Cite; List of Contributors; Introduction; Part I: RNA-Seq; Chapter 1: The Bench Scientist's Guide to Statistical Analysis of RNA-Seq Data; Chapter 2: Assembly of Non-Unique Insertion Content Using Next-Generation Sequencing; Chapter 3: RSEM: Accurate Transcript Quantification from RNA-Seq Data With or Without a Reference Genome; Part II: Microarray; Chapter 4: A Regression System for Estimation of Errors Introduced by Confocal Imaging into Gene Expression Data in Situ.
  • Chapter 5: SPACE: An Algorithm to Predict and Quantify Alternatively Spliced Isoforms Using MicroarraysChapter 6: Link-Based Quantitative Methods to Identify Differentially Coexpressed Genes and Gene Pairs; Chapter 7: Dimension Reduction with Gene Expression Data Using Targeted Variable Importance Measurement; Part III: GWAS; Chapter 8: Genome-Wide Association Study of Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis in Europe; Chapter 9: Genotyping Common and Rare Variation Using Overlapping Pool Sequencing.
  • Chapter 10: Learning Genetic Epistasis Using Bayesian Network Scoring CriteriaChapter 11: Combined Analysis of Three Genome-Wide Association Studies on vWF and FVIII Plasma Levels; Part IV: Proteomics; Chapter 12: Statistical Methods for Quantitative Mass Spectrometry Proteomic Experiments with Labeling; Chapter 13: MRCQuant: An Accurate LC-MS Relative Isotopic Quantification Algorithm on TOF Instruments; Author Notes.

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