Statistical Analysis in Proteomics [E-Book] / edited by Klaus Jung.
This valuable collection aims to provide a collection of frequently used statistical methods in the field of proteomics. Although there is a large overlap between statistical methods for the different ‘omics’ fields, methods for analyzing data from proteomics experiments need their own specific adap...
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Full text |
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Personal Name(s): | Jung, Klaus. editor |
Edition: |
1st ed. 2016. |
Imprint: |
New York, NY :
Humana Press,
2016
|
Physical Description: |
X, 313 p. 85 illus., 58 illus. in color. online resource. |
Note: |
englisch |
ISBN: |
9781493931064 |
DOI: |
10.1007/978-1-4939-3106-4 |
Series Title: |
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Methods in molecular biology ;
1362 |
Subject (LOC): |
- Introduction to Proteomics Technologies
- Topics in Study Design and Analysis for Multi-Stage Clinical Proteomics Studies
- Preprocessing and Analysis of LC-MS-Based Proteomic Data
- Normalization of Reverse Phase Protein Microarray Data: Choosing the Best Normalization Analyte
- Outlier Detection for Mass Spectrometric Data
- Visualization and Differential Analysis of Protein Expression Data Using R
- False Discovery Rate Estimation in Proteomics
- A Nonparametric Bayesian Model for Nested Clustering
- Set-Based Test Procedures for the Functional Analysis of Protein Lists from Differential Analysis
- Classification of Samples with Order Restricted Discriminant Rules
- Application of Discriminant Analysis and Cross Validation on Proteomics Data
- Protein Sequence Analysis by Proximities
- Statistical Method for Integrative Platform Analysis: Application to Integration of Proteomic and Microarray Data
- Data Fusion in Metabolomics and Proteomics for Biomarkers Discovery
- Reconstruction of Protein Networks Using Reverse Phase Protein Array Data
- Detection of Unknown Amino Acid Substitutions Using Error-Tolerant Database Search
- Data Analysis Strategies for Protein Modification Identification
- Dissecting the iTRAQ Data Analysis
- Statistical Aspects in Proteomic Biomarker Discovery.