𝔖 Bobbio Scriptorium
✦   LIBER   ✦

New Analysis for a Robust Quantification of Microarray Data

✍ Scribed by B. Hitzmann; C. Repenning; T. Scheper; M. Reck

Publisher
John Wiley and Sons
Year
2006
Tongue
German
Weight
79 KB
Volume
78
Category
Article
ISSN
0009-286X

No coin nor oath required. For personal study only.

πŸ“œ SIMILAR VOLUMES

A robust mixed linear model analysis for
A robust mixed linear model analysis for longitudinal data
✍ Paramjit S. Gill πŸ“‚ Article πŸ“… 2000 πŸ› John Wiley and Sons 🌐 English βš– 124 KB πŸ‘ 3 views

This paper describes robust procedures for estimating parameters of a mixed e!ects linear model as applied to longitudinal data. In addition to "xed regression parameters, the model incorporates random subject e!ects to accommodate between-subjects variability and autocorrelation for within-subject

A robust calibration modeling strategy f
A robust calibration modeling strategy for analysis of interference-subject spectral data
✍ Chunhui Zhao; Furong Gao; Yuan Yao; Fuli Wang πŸ“‚ Article πŸ“… 2009 πŸ› American Institute of Chemical Engineers 🌐 English βš– 368 KB πŸ‘ 1 views

## Abstract Preprocessing and correction of mixture spectra have been an important issue with regard to the removal of undesired systematic variation due to variations in environmental, instrumental, or sample conditions. In this article, a new robust calibration modeling strategy is proposed on th

Variance Component Estimation for Mixed
Variance Component Estimation for Mixed Model Analysis of cDNA Microarray Data
✍ Barbara Sarholz; Hans-Peter Piepho πŸ“‚ Article πŸ“… 2008 πŸ› John Wiley and Sons 🌐 English βš– 406 KB πŸ‘ 2 views

## Abstract Microarrays provide a valuable tool for the quantification of gene expression. Usually, however, there is a limited number of replicates leading to unsatisfying variance estimates in a gene‐wise mixed model analysis. As thousands of genes are available, it is desirable to combine inform