How can one compare group correlations for the genes, which belong to the same Gene Ontology (GO)-term given the problem that positive and negative correlated time series plot trajectories cancel each other out?
Where can I find or generate distance measures yeast gene expression based on promoter similarities / Transcription Factor Binding Site (TFBS) similarities?
Can the time series expression trajectories be predicted from TFBS and Transcription Factor (TF) ratios? If so, how? If we have expression for all 89 yeast TFs, the TFBS-distributions of the promoters for each gene using supervised machine learning?
In other words, are TF-abundancies and TFBS-distributions enough selected features to predict amount of transcription for each gene?
I know that there may be co-activators or represors, which I cannot account for.
Where can I find a cell cycle yeast time series dataset, which has transcription and translation measured at least every 10 minutes?
To find TF-abundancies we need protein instead mRNA levels. The mRNA levels changes should precede the protein level gene changes, which they are causing by about one hour.
But what if the yeast changes protein ratios and abundances by ribosomal coverage or changes in the length of the poly-AAA-tail of coding mRNA strand?
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