The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Combinatorial pattern discovery in biological sequences: The TEIRESIAS algorithm.
Abstract
MOTIVATION: The discovery of motifs in biological sequences is an important problem. RESULTS: This paper presents a new algorithm for the discovery of rigid patterns (motifs) in biological sequences. Our method is combinatorial in nature and able to produce all patterns that appear in at least a (user-defined) minimum number of sequences, yet it manages to be very efficient by avoiding the enumeration of the entire pattern space. Furthermore, the reported patterns are maximal: any reported pattern cannot be made more specific and still keep on appearing at the exact same positions within the input sequences. The effectiveness of the proposed approach is showcased on a number of test cases which aim to: (i) validate the approach through the discovery of previously reported patterns; (ii) demonstrate the capability to identify automatically highly selective patterns particular to the sequences under consideration. Finally, experimental analysis indicates that the algorithm is output sensitive, i.e. its running time is quasi-linear to the size of the generated output.
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Cites
Needleman, S. B., & Wunsch, C. D. (1970) · Journal of Molecular Biology · doi:10.1016/0022-2836(70)90057-4 · Cited by 11,288
Cited by
Miranda, K. C., Huynh, T., Tay, Y., Ang, Y.-S., Tam, W.-L., Thomson, A. M., Lim, B., & Rigoutsos, I. (2006) · Cell · doi:10.1016/j.cell.2006.07.031 · Cited by 2,063
Self-citationDNA binding sites: representation and discovery
Stormo, G. D. (2000) · Bioinformatics · doi:10.1093/bioinformatics/16.1.16 · Cited by 1,502
Non-classical protein secretion in bacteria
Bendtsen, J. D., Kiemer, L., Fausbøll, A., & Brunak, S. (2005) · BMC Microbiology · doi:10.1186/1471-2180-5-58 · Cited by 706
Antimicrobial peptides: an overview of a promising class of therapeutics
Giuliani, A., Pirri, G., & Nicoletto, S. (2007) · Open Life Sciences · doi:10.2478/s11535-007-0010-5 · Cited by 606
Probabilistic discovery of time series motifs
Chiu, B., Keogh, E., & Lonardi, S. (2003) · Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/956750.956808 · Cited by 573
Metadata
- Authors
- Rigoutsos, I., & Floratos, A.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 1998-01-01
- Volume
- 14
- Issue
- 1
- Pages
- 55-67
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2028903194
- Cited by
- 557
- References
- 1
- FWCI
- 13.57
- Type
- journal article
- Language
- en
- Open access
- closed
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- Rigoutsos, I., & Floratos, A. (1998). Combinatorial pattern discovery in biological sequences: The TEIRESIAS algorithm. Bioinformatics. https://doi.org/10.1093/bioinformatics/14.1.55
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
