6) Systematic analysis of snake neurotoxins' functional classification using a data warehousing approach.

Siew JP, Khan AM, Tan PT, Koh JL, Seah SH, Koo CY, Chai SC, Armugam A, Brusic V, Jeyaseelan K.
Bioinformatics. 2004 Dec 12;20(18):3466-80. Epub 2004 Jul 22.
PUBMED PMID: 15271784
Out link: Full-text
Impact Factor Year 2009: 4.926
No. of Citations: 9 (total): 5 (non-self) & 4 (self)

ABSTRACT:

MOTIVATION: Sequence annotations, functional and structural data on snake venom neurotoxins (svNTXs) are scattered across multiple databases and literature sources. Sequence annotations and structural data are available in the public molecular databases, while functional data are almost exclusively available in the published articles. There is a need for a specialized svNTXs database that contains NTX entries, which are organized, well annotated and classified in a systematic manner.

RESULTS: We have systematically analyzed svNTXs and classified them using structure-function groups based on their structural, functional and phylogenetic properties. Using conserved motifs in each phylogenetic group, we built an intelligent module for the prediction of structural and functional properties of unknown NTXs. We also developed an annotation tool to aid the functional prediction of newly identified NTXs as an additional resource for the venom research community.

AVAILABILITY: We created a searchable online database of NTX proteins sequences (http://research.i2r.a-star.edu.sg/Templar/DB/snake_neurotoxin). This database can also be found under Swiss-Prot Toxin Annotation Project website (http://www.expasy.org/sprot/).

This article has been cited by other articles:

1) Tamiya T, Fujimi TJ. Molecular evolution of toxin genes in Elapidae snakes. Mol Divers. 2006 Nov;10(4):529-43. Epub 2006 Nov 10. Review. PMID: 17096076

2) Koh DC, Armugam A, Jeyaseelan K. Snake venom components and their applications in biomedicine. Cell Mol Life Sci. 2006 Dec;63(24):3030-41. Review. PMID: 17103111

3) Lam, K.-T., Koh, J.L.Y., Veeravalli, B., Brusic, V. Incremental maintenance of biological databases using association rule mining. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 4146 LNBI, pp. 140-150

4) Saha S, Raghava GP. Prediction of neurotoxins based on their function and source. In Silico Biol. 2007 Apr 6;7:0025 [Epub ahead of print] PMID: 17688450

5) Olamendi-Portugal T, Batista CV, Restano-Cassulini R, Pando V, Villa-Hernandez O, Zavaleta-Martínez-Vargas A, Salas-Arruz MC, Rodríguez de la Vega RC, Becerril B, Possani LD.

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6) Paul, D., Rastogi, N., Krauss, U., Schlomann, M., Pandey, G., Pandey, J., Ghosh, A., Jain, R.K. Diversity of 'benzenetriol dioxygenase' involved in p-nitrophenol degradation in soil bacteria. Indian Journal of Microbiology. 2008, 48 (2), pp. 279-286

7) Tan Thiam Joo, Paul

Functional prediction of bioactive toxins in scorpion venom through bioinformatics

PhD Thesis, 2006

https://scholarbank.nus.edu.sg/handle/10635/15536

8) Prediction of neurotoxins by support vector machine based on multiple feature vectors.

Guang XM, Guo YZ, Wang X, Li ML.

Interdiscip Sci. 2010 Sep;2(3):241-6. Epub 2010 Jul 25.

PMID: 20658336

9) Functional prediction of snake neurotoxins

Seah SH, Kwoh CK, Brusic V, et al.

Conference Information: 9th International Conference on Control, Automation, Robotics and Vision, DEC 05-08, 2006 Singapore, SINGAPORE

2006 9th International Conference on Control, Automation, Robotics and Vision, Vols 1- 5 Pages: 2295-2298 Published: 2006