OpenStructure: an integrated software framework for computational structural biology
By Marco Biasini, Tobias Schmidt, Stefan Bienert, Valerio Mariani, Gabriel Studer, J. Haas, Niklaus Johner, A. Schenk, A. Philippsen, Torsten Schwede. 2013
166 citations recorded by the source corpus.
Current developments in the computational structural biology framework OpenStructure are presented.
Subfields: Molecular Biology
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
- Torsten Schwede
- Lorenza Bordoli
- Gabriel Studer
- Yang Zhang
- J. Haas
- Andrew M. Waterhouse
- Andriy Kryshtafovych
- Rafal Gumienny
Citations in the corpus
- SWISS-MODEL: homology modelling of protein structures and complexes (2018, positive): “SWISS-MODELisimplementedinPython and Django with Javascript and jQuery for the front-end, and Python, C++ and OpenStructure (38) for the back-end functions.”
- The SWISS-MODEL Repository—new features and functionality (2016, methodology): “ProMod3 has been implemented based on the OpenStructure (21) library and replaces ProMod-II (22) used previously.”
- SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information (2014, methodology): “The implementation of computational routines in SMTL is based on OpenStructure (17).”
- Boltz-1 Democratizing Biomolecular Interaction Modeling (2024, unknown): “In particular, we look at: All metrics were computed using OpenStructure [Biasini et al., 2013] version 2.8.0.”
- QMEANDisCo—distance constraints applied on model quality estimation (2019, methodology): “DisCo is derived from QMEANDist, a quasi-single model method that participated in the CASP9 experiment as a global quality predictor (Biasini, 2013; Kryshtafovych et al. , 2011).”
- Dynamic-Backbone Protein-Ligand Structure Prediction with Multiscale Generative Diffusion Models (2022, methodology): “The per-residue all-atom lDDT score is computed using OpenStructure [70]; the lDDT-BS score is then computed by averaging the per-residue scores for ligand binding site residues with a cutoff of 4.”
- CAMEO - Perspectives on the future of fully automated evaluation of structure prediction methods (2021, unknown): “0 (Biasini et al. 2013), as well as the MM-align-based TM-score v.”
- Assessment of ligand binding site predictions in CASP10 (2014, background): “…in protein complexes which participate in various biological process (e.g., signal transduction, cell adhesion, pattern formation, and migration)26; it contains a metal ion site at the surface that could represent a general metal ion-dependent adhesion site (MIDAS) for binding protein ligands.”
- Continuous Automated Model EvaluatiOn (CAMEO) complementing the critical assessment of structure prediction in CASP12 (2018, methodology): “Figure 1 was created with OpenStructure.(34) TheQS-score(25) is assessing the correctness of the predicted quaternary structure by considering the assembly interface as a whole.”