Bioinformatics (eBook, PDF)

The Impact of Accurate Quantification on Proteomic and Genetic Analysis and Research
Redaktion: Liu, Yu

• Format: PDF

Produktbeschreibung

This title includes a number of Open Access chapters.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.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 412
• Erscheinungstermin: 24. Februar 2014
• Englisch
• ISBN-13: 9781482246629
• Artikelnr.: 40729718

Autorenporträt

Dr. Yu Liu is a bioinformatician with special interest in next-gen sequencing and its applications. His specialties are molecular biology, DNA sequence analysis, next-gen sequencing application on gene expression analysis and comparative genomics, and microarray gene expression analysis. He is the director of the Bioinformatics Resource Center at the University of Wisconsin-Madison. He has a master's degree in computer science from the University of Wisconsin-Madison, a master's degree in developmental biology from the Chinese Academy of Science, and PhD in molecular biology from The Ohio State University.

Inhaltsangabe

Introduction. Part I: RNA-Seq. The Bench Scientist's Guide to Statistical
Analysis of RNA-Seq Data. Assembly of Non-Unique Insertion Content Using
Next-Generation Sequencing. RSEM: Accurate Transcript Quantification from
RNA-Seq Data With or Without a Reference Genome. Part II: Microarray. A
Regression System for Estimation of Errors Introduced by Confocal Imaging
into Gene Expression Data In Situ. SPACE: An Algorithm to Predict and
Quantify Alternatively Spliced Isoforms Using Microarrays. Link-Based
Quantitative Methods to Identify Differentially Coexpressed Genes and Gene
Pairs. Dimension Reduction with Gene Expression Data Using Targeted
Variable Importance Measurement. Part III: GWAS. Genome-Wide Association
Study of Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis in Europe.
Genotyping Common and Rare Variation Using Overlapping Pool Sequencing.
Learning Genetic Epistasis Using Bayesian Network Scoring Criteria.
Combined Analysis of Three Genome-Wide Association Studies on vWF and FVIII
Plasma Levels. Part IV: Proteomics. Statistical Methods for Quantitative
Mass Spectrometry Proteomic Experiments with Labeling. MRCQuant: An
Accurate LC-MS Relative Isotopic Quantification Algorithm on TOF
Instruments. Index.