Sentence examples for motif discovery process from inspiring English sources

We want our optimized HMM to also lay the foundation for a multifaceted regulatory motif discovery process.

Strategy 2 uses all available alignment information (pairwise and multiple alignments) whereas strategy 3 does not use any alignment information in the actual motif discovery process.

We present here a program called PriorsEditor, which allows users to easily construct positional priors tracks by combining various types of information and utilize these priors to potentially improve the motif discovery process (Fig. 1).

We regard the motif discovery process as distributed on two stages, where the first stage unearths motifs endowed with a certain set of properties and the second implements them in the compression.

Since network motif discovery involves computationally challenging processes, previous algorithms have focused on computational efficiency.

This extra knowledge is used during the process of motif discovery.

Moreover, the currently available online motif discovery software has limited capacity to process a small number of gene entries.

Apart from being used to narrow down the sequence search space, priors information can also be applied to post-process results after motif discovery has been carried out, for instance, by filtering out predicted binding sites that lie in areas with low priors or adjusting the prediction scores of these sites based on the priors they overlap.

Another optimization of practical interest is to speed up and find alternative ways of formalizing the discovery process of suboptimal motifs.

To date, efforts to understand how genomic DNA guides this process have focused on de novo motif discovery and known motif mapping (Ji and Wong, 2006).

We demonstrated how the G = MAT model can be applied for the discovery of process-specific TFs and motifs, for motif discovery and for GO annotation.