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Thirty targets is also the suggested minimum for motif discovery using DME [11].
Therefore, we conducted de novo motif discovery using the MEME algorithm (see Methods).
We tested this hypothesis by developing a new methodology for in silico motif discovery using FAIRE-seq coverage.
De novo motif discovery using the central 100bp of the high confidence STAT5 peaks were used to provide a single highly significant motif of 10 bp in length.
De-novo motif discovery using MEME identified a number of motifs enriched in the sequences of translationally regulated mRNAs after sucrose treatment (Table 2).
(C ) Differential motif discovery using MEME and a 50 bp sequence centered on summits of late-only vs. static ZEB1 peaks reveals adipogenic motifs: C/EBPα|C/EBPβ, NFIC and PPARG::RXR (p < 10−3, 'Materials and methods').
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Motif discovery used CisFinder (Sharov and Ko, 2009) and MEME (Machanick and Bailey, 2011) with default parameters; specific motifs were mapped back to peaks using Fuzznuc (Rice et al., 2000).
For Ubx, we used the top 300 binding peaks and performed motif discovery analysis using nestedMica [50] for the embryo and haltere data separately.
We used the DREME tool to search for enriched short motifs (up to eight bases) in the tissue-specific promoter datasets used in our promoter analysis and performed a discriminative motif discovery search using different tissue datasets as negative controls.
In this paper, we present a highly parallel formulation and implementation of the MEME motif discovery algorithm using the CUDA programming model.
These methods, however, rely on an initial motif discovery phase using generic pattern-finding TEIRESIAS software [9], which returns all shared patterns regardless of evolutionary relationships and with only crude length and complexity control.
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