Application and Algorithm: Maximal Motif Discovery for Biological Data in a Sliding Window
- 29 May 2020
- book chapter
- Published by Springer Nature
- Vol. 585, 213-224
Abstract
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 ℓ, on a sequence x of length n.Keywords
This publication has 14 references indexed in Scilit:
- MoTeX-II: structured MoTif eXtraction from large-scale datasetsBMC Bioinformatics, 2014
- DNA Replication OriginsCold Spring Harbor Perspectives in Biology, 2013
- An Efficient Algorithm for the Identification of Structured Motifs in DNA Promoter SequencesIEEE/ACM Transactions on Computational Biology and Bioinformatics, 2006
- RISOTTO: Fast Extraction of Motifs with Mismatches2006
- Weeder Web: discovery of transcription factor binding sites in a set of sequences from co-regulated genesNucleic Acids Research, 2004
- YMF: a program for discovery of novel transcription factor binding sites by statistical overrepresentationNucleic Acids Research, 2003
- Extracting regulatory sites from the upstream region of yeast genes by computational analysis of oligonucleotide frequencies 1 1Edited by G. von HeijneJournal of Molecular Biology, 1998
- The dnaA protein complex with the E. coli chromosomal replication origin (oriC) and other DNA sitesCell, 1984
- General methods of sequence comparisonBulletin of Mathematical Biology, 1984
- Nucleotide sequence of the origin of replication of the Escherichia coli K-12 chromosome.Proceedings of the National Academy of Sciences, 1979