The PSIPRED protein structure prediction server

By Liam J. McGuffin, Kevin Bryson, David T. Jones. 2000

3,889 citations recorded by the source corpus.

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In Molecular Biology

Citations in the corpus

Enhancing Evolutionary Couplings with Deep Convolutional Neural Networks (2017, methodology): “We used PSIPRED to generate one-dimensional features.”
A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction (2014, methodology): “DNSS 81.1 74.7 80.2 73.6 80.7 74.2 50.4 46.1 PSSpred 83.3 72.0 81.0 70.4 82.2 71.3 41.8 33.7 SSpro 79.6 72.6 78.8 71.9 79.2 72.3 49.6 34.0 PSIPRED 80.9 69.3 81.2 68.6 81.0 69.0 33.8 23.2 RaptorX 78.1 70.4 77.9 70.3 78.0 70.3 45.6 33.0 Scores show the average accuracy of secondary structure predic”
RaptorX-Property: a web server for protein structure property prediction (2016, methodology): “…prediction as an example, when template information is not used and only sequence profile is considered, so far the best Q3 accuracy is ∼ 80% obtained by a few predictors such as PSIPRED (8) and JPRED (7), which is significantly lower than the estimated prediction accuracy limit 88–90% (9).”
PONDR-FIT: A Meta-Predictor of Intrinsically Disordered Amino Acids (2010, methodology): “A sequential analysis about the influence of number of components on the accuracy, which was previously applied in PsiPred [50], is very interesting.”
EVA: evaluation of protein structure prediction servers (2003, background): “... G Raghava (40) Jpred http://jura.ebi.ac.uk:8888/ JA Cuff and GJ Barton (41) PHDsec http://cubic.bioc.columbia.edu/predictprotein B Rost and C Sander (42) PHDpsi http://cubic.bioc.columbia.edu/predictprotein D Przybylski and B Rost (43) PROF_king http://www.aber.ac.uk/~phiwww/prof/ M Ouali and R ”
BASys: a web server for automated bacterial genome annotation (2005, methodology): “Various sequence analyses are also performed on the query sequence, including protein family analysis with Pfam (15), sequence motif analysis with PROSITE (16), signal peptide and transmembrane domain prediction with PredictSPTM (J. Cruz, unpublished data), and predicted secondary structure with PSI”
The Wolbachia Genome of Brugia malayi: Endosymbiont Evolution within a Human Pathogenic Nematode (2005, methodology): “], and transmembrane helices were predicted using the MEMSAT program [”