Automated server predictions in CASP7

By J. Battey, Jürgen Kopp, Lorenza Bordoli, Randy J. Read, Neil D. Clarke, Torsten Schwede. 2007

115 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computational Biology & Bioinformatics

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Citations in the corpus

lDDT: a local superposition-free score for comparing protein structures and models using distance difference tests (2013, methodology): “In CASP7, the first scores based on local atomic interactions were introduced in the form of HBscore, which quantifies the fraction of hydrogen bond interactions in the target protein correctly reproduced in the model (Battey et al ., 2007; Kopp et al ., 2007).”
Fast and accurate automatic structure prediction with HHpred (2009, background): “Relative to the old HHpred2 server, which ranked second in CASP7 [ 14 ], the improvements are split up as follows: (1) The removal of bugs in the old server led to an increase in the cumulative GDT TS score of 0:5%.”
The Protein Model Portal (2008, background): “…standards for describing the reliability and limitations of the most commonly used experimental structure determination techniques have been established, the spectrum of reliability and applicability of current modeling methods is broad and the level of uncertainty is signiﬁcantly higher [19, 20].”
Protein structure homology modeling using SWISS-MODEL workspace (2008, background): “Details about the participating servers and public accessibility are given in Table 1 of ref”
Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations (2021, methodology): “As an independent structure assembly pipeline, I-TASSER was tested in former CASPs and consistently ranked as one of the most accurate methods in the past decade (Battey et al., 2007; Kryshtafovych et al., 2018).”
SP5: Improving Protein Fold Recognition by Using Torsion Angle Profiles and Profile-Based Gap Penalty Model (2008, methodology): “SPARKS, SP 3 , and SP 4 were ranked among the top performers for automatic servers in recent CASP 6 [13,14] and 7 [12,3].”
Assessment of ligand binding site predictions in CASP10 (2014, background): “The accuracy of predictions of three-dimensional structures is assessed as part of the template-based (TBM) and free-modeling (FM) categories,13–16 which includes the accuracy of binding site coordinates.17 ,18 Function prediction (FN) was introduced as a new category in CASP6.”
I-TASSER server for protein 3D structure prediction (2008, unknown): “The average GDT_TS [5] or TM-score [6] of all 124 targets/domains is at least 5% higher than the second best server and comparable with the best human-expert predictions [7].”
Automated Protein Structure Modeling with SWISS-MODEL Workspace and the Protein Model Portal (2012, background): “Finally, from a theoretical perspective, automatic procedures ensure the reproducibility of the modeling methods by excluding individual human bias, which is a pre-requisite for the assessment and comparison of their reliability and accuracy (22, 38).”
I-TASSER: a unified platform for automated protein structure and function prediction (2010, background): “Recent community-wide critical assessment of protein structure prediction (CASP) experiment”
Assessment of template based protein structure predictions in CASP9 (2011, methodology): “While earlier editions of CASP focused mainly on C a based measures, in CASP7 all-atom measures and checks for physical plausibility were introduced,18,21 and even stronger emphasized in CASP8.”
The SWISS-MODEL Repository and associated resources (2008, background): “During the CASP7 experiment, it became apparent that the best fully automated modelling methods have improved to a level where they challenge most human predictors in producing the most accurate models (13–15).”
Progress and challenges in protein structure prediction. (2008, methodology): “The profile-alignment-based methods demonstrated advantages in several recent blind tests [21,22,23 ].”