Rank-Scaled Metric Clustering of Amino-Acid Sequences

Mathematical Biology & Bioinformatics. 2012;7(1):345-359.

doi: 10.17537/2012.7.345.

1. Rudakov KV, Torshin IYu. Doklady Akademii Nauk. 2011;441(1):24-28. (In Rus.).
2. Rudakov KV, Torshin IYu. The motif information analysis based on the solvability criterion for the protein secondary structure recognition. Informatics and Its Applications. 2012;6(1). (In Rus.).
3. About Nucleotide And Protein Sequence Formats. http://www.ebi.ac.uk/help/formats.html (accessed 17 May 2012).
4. UniProtKB protein knowledgebase: example of a record. http://www.uniprot.org/uniprot/Q08753 (accessed 20 November 2011).
5. Huang ZA. Fast Clustering Algorithm to Cluster Very Large Categorical Data Sets in Data Mining. Cooperative Research Centre for Advanced Computational Systems. 1997.
6. Cardot H, Cenac P, Monnez J-M. Fast clustering of large datasets with sequential k-medians: a stochastic gradient approach. arXiv. 2011:1101.4179. http://arxiv.org/abs/1101.4179 (accessed 16 May 2012).
7. Seber GAF. Multivariate Observations. Hoboken, NJ: John Wiley & Sons, Inc; 1984.
8. Spath H. Cluster Dissection and Analysis: Theory, FORTRAN Programs, Examples. Translated by J. Goldschmidt. New York: Halsted Press; 1985.
9. Wei C-P, Lee Y-H, Hsu C-M. Empirical comparison of fast partitioning-based clustering algorithms for large data sets. Expert Systems with Application. 2003;24(4).
10. Giannopoulos P, Knauer C, Wahlstrom M, Werner D. Hardness of discrepancy computation and epsilon-net verification in high dimension. arXiv. 2011:1103.4503. http://arxiv.org/abs/1103.4503 (accessed 16 May 2012).
11. Levenshtein VI. Binary codes capable of correcting deletions, insertions, and reversals. Soviet Physics Doklady. 1966;10:707–710.
12. UniRef DataBase. http://www.uniprot.org/uniref/ (accessed 13 May 2012).
13. Protein knowledgebase UniprotKB. http://www.uniprot.org (accessed 13 May 2012).
14. Kabsch W, Sander C. Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers. 1983;22(12):2577-637. doi: 10.1002/bip.360221211
15. Marschall T. Algorithms and Statistical Methods for Exact Motif Discovery: PhD Thesis. Dortmund; 2011. https://eldorado.tu-dortmund.de/bitstream/2003/27760/1/dissertation.pdf (accessed 16 May 2012).
16. Li G, Chan TM, Leung KS, Lee KH. A Cluster Refinement Algorithm for Motif Discovery. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2010;7(4):654-668. doi: 10.1109/TCBB.2009.25