Sentence examples for based on sequence motif from inspiring English sources
In case of non-mesodermal enhancers, however, the best performing classifier is the one based on sequence motif information.
These results demonstrated that a novel and functional βMP can be successfully engineered through strand replacement based on sequence motif analysis and stability calculation.
However, based on sequence motif recognition software, [20] modelled the Delta1/Notch1 pathway under the assumption that rbpj itself is repressed by the Hes1 homodimers containing 3 N box binding sites and 3 RBPJ binding sites.
Note that, as would be expected, virtually all clusters are identified based on sequence motif information, and that no cluster is enriched in the ChIP/chip data of naive c35 mutant cells.
We ranked biological processes in terms of significance for all functional enrichment tests and calculated the numbers of processes in common for increasing length of ranked lists for results based on sequence motif versus ChIP/chip results from naive, BaP-treated, TCDD-treated, and negative control c35 cells.
To train machine learning models, negative data is of importance yet hard to come by; therefore, we recently started to employ pre-miRNAs from one species as positive data versus another species' pre-miRNAs as negative examples based on sequence motifs and k-mers.
Sequences were analyzed with KeyDNAtools (http://keydnatools.com/), an application which provides taxonomic affiliation and chimera detection (Table S1) based on sequence motifs [5].
Which of the potential binding sites a transcription factor actually binds depends on the state of the cells, whereas computational prediction based on sequence motifs will not have this kind of bias.
Taken together, existing studies suggest that an in silico approach based on sequence motifs, characterizing phosphorylation sites and distal sites, may be useful for predicting the substrates of kinases that have not been well-characterized by existing methods.
Netphos [ 12] was the first predictor to use neural networks in 1999, outperforming phosphorylation site identification based on sequence motifs alone.
