"The fluxes that we generate are larger than natural fluxes.
To exclude the possibility that the lack of effect of the SnoN (KdR) on E-cadherin suppression by TGFβ is due to impairment of potential modifications other than sumoylation, we generated a distinct SUMO loss of function SnoN mutant (SnoN (EdA)) in which Glutamates 52 and 385 within SUMO consensus motifs (ψKXE) in SnoN were converted to alanine residues (Figure 6A).
Firstly, we tested separately the two alternative hypotheses: that the correlation of a regulator-target pair is greater than zero and that the correlation is less than zero, and we generated separate null distributions for the two conditions.
To contrast the current state of known chemistry ('now') with that from a little more than 40 years ago ('then'), we generated atom environments of radius r = 1 for all structures in PubChem Compound.
To identify the genome-wide distribution of SF2/ASF binding sites around exon splice sites, for each exon from a protein coding gene (greater than 100 bp), we generated a composite sequence made of the 75 bp upstream of the 3' splice site, the 5' exonic 25 bp, the 50 bp from the middle of the exon, the 25 bp 3' exonic and 75 bp downstream of the 5' splice site.
For all phosphoserines and, separately, for the subset of phosphoserines observed in more than one experiment, we generated 10000 random sets of non-modified serines of appropriate size.
Because some genes were identified in more than one strain, we generated deletions that enabled us to test a total of 44 candidate alleles by reciprocal hemizygosity analysis.
"We never had more ball possession than our rivals, but we generated more scoring opportunities than they did".
In less than two months time, we generated ZFNs for target sites in five different biologically important genes.
Because geolocation errors are much larger than for ARGOS data, we generated 500 particles per record instead of 50 with ARGOS data (empirically).
