The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Porter: a new, accurate server for protein secondary structure prediction
Open accessAbstract
UNLABELLED: Porter is a new system for protein secondary structure prediction in three classes. Porter relies on bidirectional recurrent neural networks with shortcut connections, accurate coding of input profiles obtained from multiple sequence alignments, second stage filtering by recurrent neural networks, incorporation of long range information and large-scale ensembles of predictors. Porter's accuracy, tested by rigorous 5-fold cross-validation on a large set of proteins, exceeds 79%, significantly above a copy of the state-of-the-art SSpro server, better than any system published to date. AVAILABILITY: Porter is available as a public web server at http://distill.ucd.ie/porter/ CONTACT: gianluca.pollastri@ucd.ie.
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Cites
Gapped BLAST and PSI-BLAST: a new generation of protein database search programs
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Prediction of Protein Secondary Structure at Better than 70% Accuracy
Rost, B., & Sander, C. (1993) · Journal of Molecular Biology · doi:10.1006/jmbi.1993.1413 · Cited by 2,910
GenTHREADER: an efficient and reliable protein fold recognition method for genomic sequences
Jones, D. T. (1999) · Journal of Molecular Biology · doi:10.1006/jmbi.1999.2583 · Cited by 895
Pollastri, G., Przybylski, D., Rost, B., & Baldi, P. (2002) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.10082 · Cited by 743
Self-citationExploiting the past and the future in protein secondary structure prediction
Baldi, P., Brunak, S., Frasconi, P., Soda, G., & Pollastri, G. (1999) · Bioinformatics · doi:10.1093/bioinformatics/15.11.937 · Cited by 497
Self-citationCoupled prediction of protein secondary and tertiary structure
Meiler, J., & Baker, D. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1831973100 · Cited by 197
Rosetta predictions in CASP5: Successes, failures, and prospects for complete automation
Bradley, P., Chivian, D., Meiler, J., Misura, K. M. S., Rohl, C. A., Schief, W. R., Wedemeyer, W. J., Schueler-Furman, O., Murphy, P., Schonbrun, J., et al. (2003) · Proteins: Structure, Function, and Genetics · doi:10.1002/prot.10552 · Cited by 181
EVA: Large-scale analysis of secondary structure prediction
Rost, B., & Eyrich, V. A. (2001) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.10051 · Cited by 134
Cited by
JPred4: a protein secondary structure prediction server
Drozdetskiy, A., Cole, C., Procter, J., & Barton, G. J. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv332 · Cited by 1,744
ESpritz: accurate and fast prediction of protein disorder
Walsh, I., Martin, A. J. M., Di Domenico, T., & Tosatto, S. C. E. (2012) · Bioinformatics · doi:10.1093/bioinformatics/btr682 · Cited by 532
Comparative sequence analysis of leucine-rich repeats (LRRs) within vertebrate toll-like receptors
Matsushima, N., Tanaka, T., Enkhbayar, P., Mikami, T., Taga, M., Yamada, K., & Kuroki, Y. (2007) · BMC Genomics · doi:10.1186/1471-2164-8-124 · Cited by 393
Deep learning methods in protein structure prediction
Torrisi, M., Pollastri, G., & Le, Q. (2020) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2019.12.011 · Cited by 284
Self-citationGuu, T. S. Y., Liu, Z., Ye, Q., Mata, D. A., Li, K., Yin, C., Zhang, J., & Tao, Y. J. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0904848106 · Cited by 255
Metadata
- Authors
- Pollastri, G., & McLysaght, A.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2004-12-07
- Volume
- 21
- Issue
- 8
- Pages
- 1719-1720
- ISSN
- 0266-7061 (ISSN-L)
- 1367-4803
- 1460-2059
- OpenAlex
- W2046192291
- Cited by
- 469
- References
- 12
- FWCI
- 6.78
- Type
- journal article
- Language
- en
- Open access
- bronze
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