Sentence examples for datasets were identified by from inspiring English sources
Differences between Tex19.1 −/− and control littermate datasets were identified by linear modelling with limma (71), using false discovery rate-adjusted P-values to determine statistical significance.
Similarly, pathways significantly enriched with the DEG datasets were identified by mapping all differentially expressed genes to terms in the KEGG database using the hypergeometric test with a p-value <0.05.
Orthologs for each of the proteins in the positive and negative datasets were identified by a reciprocal top hit PSI-BLAST [ 49] search against the sequences of eukaryotes from two databases, SWISSPROT (April 2009) [ 47] and UNIPROT (April 2009) [ 48].
Given the poor overlap of genes reported as being differentially expressed during drought stress in different studies (see [ 11, 12, 36]), genes regulated by drought in our datasets were identified by comparing probe intensity values from individual channels between stage 2 and stage 0 in Col-0.
Another set of miRNAs not expressed in leaf and bud datasets was identified by querying miRBase plant sequences against the peach genome using Patscan as described above.
Indeed, additional QTL, i.e. QTL that were not detected when analyzing the whole dataset, were identified by analyzing the four within-condition datasets separately.
Rhythmic expression waveforms within the normalized dataset were identified by analysis with the COSOPT curve fitting algorithm and the pattern matching function HAYSTACK.
This indicates that 85% of the reference dataset was identified by the extracted drain data, that 85% of the extracted drains were matched by the reference data and 71% of the matched drains contributed to the entire extraction and reference drain network.
The themes or categories that are most powerful in representing the entire dataset are identified by constant comparisons between individual accounts.
