Combining all results and knowing the interaction of each parameter with K*, a final expression is extracted using a multivariate regression analysis. .
Information on the noise of the yeast protein expression is extracted from the Integrate Single-cell Proteomic Analysis data [ 74].
Log2 transformed estimates of gene-level expression were extracted for analysis with corresponding expression status values indicating whether the genes were detected above background level.
The candidate genes were searched for on the UniGene database (build #92) and information on the ESTs (number of ESTs, sequence, overlap) and tissue of expression were extracted from the database for each cattle prohormone gene.
Cell type specific patterns of mRNA expression were extracted from the Genome Novartis Foundation SymAtlas data set [ 20], which measured 79 human tissue samples and cell lines (2 replicates each) using Affymetric GeneChip HG-133U arrays [ 21].
Gene expressions were extracted from oligonucleotide probes by a perfect-match model using dChip software (www.dChip.org) and gene expression values were log-transformed prior to any calculations.
Statistically significant differential expressions were extracted, and more than 40 fold change were listed.
For both microarray datasets, the gene expressions were extracted from the.
Gene expressions were extracted from the.CEL files and normalized using the Robust Multichip Average method [ 23] by running an R [ 24] script, based on the aroma package [ 25].
