Gene sets enrichment analysis of candidate gene list is a commonly used statistical technique to reveal the underlying functional mechanisms based on large collections of functional annotations.
The application of text mining technologies based on large collections of known texts, such as the MEDLINE data base, has become especially popular in the area of biological and medical information processing [ 1, 2].
Recent studies based on large collections of microarray data further suggested that gene expression divergence was associated with the evolution of aerobic fermentation (Ihmels et al. 2005; Field et al. 2009; Lin and Li 2011a).
Our preliminary computations based on large collection of human microarray data indicated difficulties identifying profiles of bimodal expression due to a great degree of subject variability and noise.
Based on large-scale collections of full-length cDNAs [ 21- 24], our group constructed DBTSS, database of transcriptional start sites [ 25, 26], which enabled the reliable identification, annotation and analysis of promoter regions [ 27- 29].
The computer simulation protocol based on larger taxon sets and larger collections of source trees enables both comparison of the relative accuracy and running time performances of S uperT riplets, t-MRP, b-MRP and TILI, and validation of their previously discussed properties.
These findings caution that selection of molecular markers for epidemiological typing should be based on large and globally representative strain collections.
The first, also known as sensor-oriented, is based on large-scale sensors deployment targeting the collection of accurate sensory data.
More gene expression studies need to be undertaken, however, that are based on a larger collection of gene sequences in order to sort out genes that are expressed in response to various stimuli and during development.
Based on the large collections of transcription data available today, we have shown that transcription in mammals does not initiate randomly over the entire genome.
