Affiliation:
1. University of Turku, Turku, Finland
Abstract
Visual inspection can help reveal patterns that would be computationally rather difficult to reveal. We consider three different algorithms for visualizations of a DNA sequence and its nucleotide content: random walk, fractal and visualization based on the entropy-like parameters calculated using a sliding window. We present a program that uses these three methods and visualizes either the whole of a given sequence, or specified fragments. It also provides facilities to compare visualizations obtained for different sequences/fragments. Random walk visualization considers the sequence symbol-by-symbol; the other two methods also take into account how well nucleotides are "mixed" in the sequence. It allows an easy visualization of repeated patterns, segments with a high/low content of some nucleotides, such as CG-islands, etc. The program also helps to identify regions of interest for further study.
Publisher
Association for Computing Machinery (ACM)
Cited by
2 articles.
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1. Visualization of Repeated Patterns in Multivariate Discrete Sequences;2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM);2020-12-07
2. Probabilistic NeuroScale for Uncertainty Visualisation;2009 13th International Conference Information Visualisation;2009-07