Scalable web services for the PSIPRED Protein Analysis Workbench

By Daniel W. A. Buchan, Federico Minneci, Timothy Nugent, Kevin Bryson, David T. Jones. Nucleic Acids Res., 2013

1,359 citations recorded by the source corpus.

Here, we present the new UCL Bioinformatics Group’s PSIPRED Protein Analysis Workbench. The Workbench unites all of our previously available analysis methods into a single web-based framework. The new web portal provides a greatly streamlined user interface with a number of new features to allow users to better explore their results. We offer a number of additional services to enable computationally scalable execution of our prediction methods; these include SOAP and XML-RPC web server access and new HADOOP packages. All software and services are available via the UCL Bioinformatics Group website at http://bioinf.cs.ucl.ac.uk/.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/61d090d329434e8edfc8c08b34c61a0c7b378fb8

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Citations in the corpus

ModFOLD6: an accurate web server for the global and local quality estimation of 3D protein models (2017, methodology): “Thus, SSA = p CHE , where, p CHE is simply the p-value from PSIPRED for the secondary structure state––coil (C), helix (H) or strand (E)––of the residue in the model according to DSSP.”
DFLpred: High-throughput prediction of disordered flexible linker regions in protein sequences (2016, neutral): “We excluded DP00688 sequence that was too long (>18 000 residues) to predict with the PSIPRED (Buchan et al., 2013) to generate secondary structure.”
The s2D method: simultaneous sequence-based prediction of the statistical populations of ordered and disordered regions in proteins. (2015, methodology): “It is performed against the UniRef90 dataset [72], which was filtered to remove trans-membrane segments, coiled-coil and low-complexity regions using the pfilt program distributed with PSIPRED [73].”
The PSIPRED Protein Analysis Workbench: 20 years on (2019, methodology): “The DomSerf and BioSerf pipelines remain as previously published (10).”
Feedback GAN (FBGAN) for DNA: a Novel Feedback-Loop Architecture for Optimizing Protein Functions (2018, methodology): “In order to optimize the synthetic genes for secondary structure, a wrapper was written around the PSIPRED predictor of secondary structure [4].”
SSpro/ACCpro 5: almost perfect prediction of protein secondary structure and relative solvent accessibility using profiles, machine learning and structural similarity (2014, methodology): “Third, even the most popular predictors still actively updated, like DISTILL (Mirabello and Pollastri, 2013) or PSIPRED (Buchan et al ., 2013), do not come with a sequence-based structural similarity module.”
Serum Albumin Domain Structures in Human Blood Serum by Mass Spectrometry and Computational Biology (2015, methodology): “We employed the following computational domain boundary prediction methods: DoBo (30), Threa-dom (31) and the domain boundary module from the PSIPRED (32) server.”
Comprehensive review of methods for prediction of intrinsic disorder and its molecular functions (2017, methodology): “DISOPRED3 and DISOPRED2 are now embedded into the PSIPRED platform [107] that also provides predictions of protein structure, Comprehensive review of methods for prediction of intrinsic disorder and its molecular.”
Genome3D: exploiting structure to help users understand their sequences (2014, methodology): “DomSerf (2) Jones UCL Prediction: Models CATH FUGUE (3) Blundell Cambridge Prediction: Annotations CATH/SCOP Gene3D (4) Orengo UCL Prediction: Annotations CATH pDomTHREADER (5) Jones UCL Prediction: Annotations CATH”