Sentence examples for database filter from inspiring English sources
FlyBase [ 44] was used as a database filter in the GO analysis.
Gene ontology (GO) classifications were performed at http://amigo.geneontology.org with the database filter set as GeneDB S. pombe.
The following AmiGO program settings were used: "Database Filter": "TAIR"; "Maximum p-value": "0.01"; Minimum number of gene products": "10% of input gene set".
The resulting list of au2 gene IDs with their corresponding Fbpp ID was merged to the Drosophila annotations from FlyBase in R. GO term enrichment was performed with AmiGO using the orthologs/homologs from the above list and FlyBase as database filter (Carbon et al., 2009).
We performed a BLASTp query (SIB BLAST Network Service) with the protein weight matrix BLOSUM62, with the following settings: (the E threshold = 10 (number of expected matches in a random database), "Filter the sequence for low-complexity regions" and "Gapped alignment" http://www.clustal.org[ 21].
Gene ontology classifications were classified at http://amigo.geneontology.org with the database filter set as GeneDB S. pombe with a threshold of maximum p value of 0.05 and minimum number of gene products of 2. We selected for publication only the biological process classifications.
Previously, we developed a database filtering technology that enabled us to design a potent anti-Staphylococcal peptide DFTamP1.
Click here to see our database filtered for well-formed examples exhibiting negative inversion without negative concord in African American English.
Click here to see the database filtered for well-formed examples exhibiting negative inversion without negative concord in varieties other than African American English.
Finally, we combined a machine learning approach using unambiguous MLR-QSAR model with PubChem database filtering concept to provide a rustic ligand-based virtual screening protocol.
After applying the BinBase database filtering, 366 metabolites passed stringent analytical quality control measures, and used for comparisons of diabetic vs. non-diabetic and UCP3 g/g vs. UCP3 g/a plasma metabolomic profiling.
