Sentence examples for methods for motif from inspiring English sources

Methods for motif discovery, for CRM prediction, and for the use of multiple genomes are compared through leave-one-out cross-validation (LOOCV) (see Figure 1).

Current methods for motif comparison typically involve a similarity metric for column-to-column comparison and a method to find the optimal position alignment between the two compared motifs [8].

The majority of current methods for motif comparison involve a similarity metric for column-to-column comparison and a method to find the optimal position alignment between the two compared motifs.

We compare the performance of our approach to previously described methods for motif and module discovery, and show that the pipeline supports detecting biologically relevant motif modules that are not easily discovered by other methods.

This can been done, for example, using the N-local-decoding approach [ 26, 27] or other methods for motif finding.

However, existing methods for motif finding suffer from high false positive rates and slow speed, and it's difficult to evaluate the performance of these methods systematically.

Based on this assumption, numerous methods for motif-based TF binding site and TF target gene prediction have been developed that utilize sets of orthologous sequences from multiple species.

To this end we have developed DEMON, a novel method for motif detection.

In this paper we present a new alignment-free method for motif comparison, which was largely inspired by the strategies for alignment-free sequence comparisons [19].

We chose the symmetric method for motif comparisons in addition to the standard asymmetric method because the former method would take into account the song syntax (i.e. syllable order) as well as the acoustic features of individual syllables.

Dreme is a recently developed popular method for motif discovery in ChIP-seq datasets.