QMEAN: A comprehensive scoring function for model quality assessment

By Pascal Benkert, Silvio C. E. Tosatto, Dietmar Schomburg. 2008

1,002 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology

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Citations in the corpus

Outcome of a Workshop on Applications of Protein Models in Biomedical Research (2009, background): “probabilities, and solvation properties (Benkert et al., 2008; Bhattacharya et al., 2008; Pettitt et al., 2005; Shen and Sali, 2006; Sippl, 1993; Wallner and Elofsson, 2003).”
ProQ3D: improved model quality assessments using deep learning (2016, methodology): “We have also compared our methods with two other state-of-the-art methods: Qmean (Benkert et al., 2008) and Qprob (Cao and Cheng, 2016), as well as a reference consensus method Pcons (Lundstrom et al.”
Improved model quality assessment using ProQ2 (2012, background): “QMEAN (S) Potential of mean force, top-ranked single MQAP in CASP8 and CASP9 [18]”
Protein structure homology modeling using SWISS-MODEL workspace (2008, neutral): “As a global indicator of the quality of a given model, the results of QMEA”
ProQ3: Improved model quality assessments using Rosetta energy terms (2016, background): “All the features from three predictors are put together with the sequencedependent features that are common to all three (RSA, SS, Cons) into a new SVM that predicts the score.”
Optimal contact definition for reconstruction of Contact Maps (2010, methodology): “[8] used the same residue burial measure and surprisingly found that a cut-off of 9Å was optimal, possibly due to differences in normalisation procedures.”
The ModFOLD4 server for the quality assessment of 3D protein models (2013, methodology): “In the past decade, machine learning-based QA programs, such as early versions of ProQ (8), QMEAN (9) and ModFOLD (10), have been used to increase the accuracy of predicted global model quality, using various combinations of structural features and/or a consensus of individual energy potentials.”
QMEAN server for protein model quality estimation (2009, methodology): “The QMEAN server provides access to both kind of methods, giving the user the opportunity to choose between the composite scoring function QMEAN (6) (which stands for Qualitative Model Energy ANalysis) and the clustering method QMEANclust (32) building on it.”