Publication: AlcoR: alignment-free simulation, mapping, and visualization of low-complexity regions in biological data
AlcoR: alignment-free simulation, mapping, and visualization of low-complexity regions in biological data
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Silva, J. M., Qi, W., Pinho, A. J., & Pratas, D. (2022). AlcoR: alignment-free simulation, mapping, and visualization of low-complexity regions in biological data. GigaScience, 12, giad101. https://doi.org/10.1093/gigascience/giad101
Abstract
Abstract
Abstract
Background: Low-complexity data analysis is the area that addresses the search and quantification of regions in sequences of elements that contain low-complexity or repetitive elements. For example, these can be tandem repeats, inverted repeats, homopolymer tails, GC-biased regions, similar genes, and hairpins, among many others. Identifying these regions is crucial because of their association with regulatory and structural characteristics. Moreover, their identification provides positional and quantity information where standard ass
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Creators (Authors)
- Silva, Jorge M
- Qi, Weihong
- Pinho, Armando J
- Pratas, Diogo
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Citations
Silva, J. M., Qi, W., Pinho, A. J., & Pratas, D. (2022). AlcoR: alignment-free simulation, mapping, and visualization of low-complexity regions in biological data. GigaScience, 12, giad101. https://doi.org/10.1093/gigascience/giad101
