The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
BindN: a web-based tool for efficient prediction of DNA and RNA binding sites in amino acid sequences
Open accessAbstract
BindN (http://bioinformatics.ksu.edu/bindn/) takes an amino acid sequence as input and predicts potential DNA or RNA-binding residues with support vector machines (SVMs). Protein datasets with known DNA or RNA-binding residues were selected from the Protein Data Bank (PDB), and SVM models were constructed using data instances encoded with three sequence features, including the side chain pK(a) value, hydrophobicity index and molecular mass of an amino acid. The results suggest that DNA-binding residues can be predicted at 69.40% sensitivity and 70.47% specificity, while prediction of RNA-binding residues achieves 66.28% sensitivity and 69.84% specificity. When compared with previous studies, the SVM models appear to be more accurate and more efficient for online predictions. BindN provides a useful tool for understanding the function of DNA and RNA-binding proteins based on primary sequence data.
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Cites
The use of the area under the ROC curve in the evaluation of machine learning algorithms
Bradley, A. P. (1997) · Pattern Recognition · doi:10.1016/s0031-3203(96)00142-2 · Cited by 7,217
Luscombe, N. M. (2001) · Nucleic Acids Research · doi:10.1093/nar/29.13.2860 · Cited by 981
Cited by
RNA Binding to CBP Stimulates Histone Acetylation and Transcription
Bose, D. A., Donahue, G., Reinberg, D., Shiekhattar, R., Bonasio, R., & Berger, S. L. (2017) · Cell · doi:10.1016/j.cell.2016.12.020 · Cited by 426
Rao, H. B., Zhu, F., Yang, G. B., Li, Z. R., & Chen, Y. Z. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr284 · Cited by 359
Identification of DNA-binding proteins using support vector machines and evolutionary profiles
Kumar, M., Gromiha, M. M., & Raghava, G. P. (2007) · BMC Bioinformatics · doi:10.1186/1471-2105-8-463 · Cited by 278
Retinoic acid-gated sequence-specific translational control by RARα
Poon, M. M., & Chen, L. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0807740105 · Cited by 138
Walia, R. R., Xue, L. C., Wilkins, K., El-Manzalawy, Y., Dobbs, D., & Honavar, V. (2014) · PLoS ONE · doi:10.1371/journal.pone.0097725 · Cited by 132
“BindN [34] An SVM classifier that uses hydrophobicity, side chain pKa, molecular mass and PSSMs for predicting RNA-binding residues.”
Method
Metadata
- Authors
- Wang, L., & Brown, S. J.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2006-07-01
- Volume
- 34
- Issue
- Web Server
- Pages
- W243-W248
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W1971894358
- Cited by
- 417
- References
- 2
- FWCI
- 6.63
- Type
- journal article
- Language
- en
- Open access
- gold
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- Wang, L., & Brown, S. J. (2006). BindN: a web-based tool for efficient prediction of DNA and RNA binding sites in amino acid sequences. Nucleic Acids Research. https://doi.org/10.1093/nar/gkl298
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