Author: Alshammary, Miznah H.; Iliopoulos, Costas S.; Mohamed, Manal; Vayani, Fatima
Title: Application and Algorithm: Maximal Motif Discovery for Biological Data in a Sliding Window Cord-id: d6qmy8ay Document date: 2020_5_4
ID: d6qmy8ay
Snippet: Since the discovery of motifs in molecular sequences for real genomic data, research into this phenomenon has attracted increased attention. Motifs are relatively short sequences that are biologically significant. This paper utilises the bioinformatics application of the algorithm outlined in [5], testing it using real genomic data from large sequences. It intends to implement bioinformatics application for real genomic data, in order to discover interesting regions for all maximal motifs, in a
Document: Since the discovery of motifs in molecular sequences for real genomic data, research into this phenomenon has attracted increased attention. Motifs are relatively short sequences that are biologically significant. This paper utilises the bioinformatics application of the algorithm outlined in [5], testing it using real genomic data from large sequences. It intends to implement bioinformatics application for real genomic data, in order to discover interesting regions for all maximal motifs, in a sliding window of length â„“, on a sequence x of length n.
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