The Computational Crystallography Toolbox: crystallographic algorithms in a reusable software framework

By R. Grosse-Kunstleve, Nicholas K. Sauter, Nigel W. Moriarty, Paul D. Adams. 2002

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In Materials Chemistry

Citations in the corpus

Towards automated crystallographic structure refinement with phenix.refine (2012, positive): “Most of the modules are available through the open- source CCTBX libraries (Grosse-Kunstleve & Adams, 2002; Grosse-Kunstleve et al., 2002).”
Overview of the CCP4 suite and current developments (2011, positive): “…set of libraries has since expanded to cover a wider range of crystallographic tasks, in particular with the addition of the Clipper library (Cowtan, 2003), the MMDB library (Krissinel et al., 2004) and the CCTBX library (Grosse-Kunstleve et al., 2002) from the PHENIX project (Adams et al., 2010).”
Structure validation in chemical crystallography (2009, unknown): “Most of the symmetry handling in the program uses the cctbx library (Grosse-Kunstleve et al., 2002).”
DIALS: implementation and evaluation of a new integration package (2018, methodology): “DIALS is built upon the cctbx library (Computational Crystallography Toolbox; Grosse-Kunstleve et al., 2002) and benefits from a substantial foundation of crystallographic and mathematical code, a robust build mechanism and a development platform using hybrid Python/C++ (Abrahams & Grosse-Kunstleve,”
The Phenix Software for Automated Determination of Macromolecular Structures (2011, methodology): “Many of the fundamental crystallographic building blocks, such as data objects and tools for their manipulation, are provided by the Computational Crystallography Toolbox (cctbx)[26].”
A new default restraint library for the protein backbone in Phenix: a conformation-dependent geometry goes mainstream (2016, methodology): “…object and incorporation into other applications following the simple example of the Python program mmtbx.cdl_lookup (Moriarty, Adams et al., 2014) in the open-source cctbx (Grosse-Kunstleve et al., 2002), which will display the restraints for a triplet of amino acids and pair of backbone angles.”
Graphical tools for macromolecular crystallography in PHENIX (2012, methodology): “For PHENIX a combination of Python (Van Rossum & Drake, 2003) and C++ (Stroustrup, 2000) is used (Grosse-Kunstleve et al. , 2002; Adams et al. , 2010).”
Phaser.MRage: automated molecular replacement (2013, methodology): “MRage uses a recently developed opensource library module in the Computational Crystallography Toolbox (cctbx; Grosse-Kunstleve et al., 2002) that allows programs to use multiple processors (CPUs or CPU cores) either in the local machine or in clusters accessible through batch submission queues…”
On the handling of atomic anisotropic displacement parameters (2002, methodology): “The benefits of this tight combination of a statically typed compiled language (C++) with a dynamically typed interpreted language (Python) are discussed in depth by Grosse-Kunstleve et al. (2002).”
Decision making in xia2 (2013, methodology): “Finally, the cctbx toolbox (Grosse-Kunstleve et al., 2002) is also extensively used in the analysis to allow lower level calculations to be performed in the xia2 code itself.”
Solving the scalability issue in quantum-based refinement: Q|R#1. (2017, methodology): “Q|R interfaces to the cctbx open-source project (Grosse-Kunstleve et al., 2002) to compute the various quantities needed for refine- ment.”
Q|R: quantum-based refinement. (2017, methodology): “Q|R uses the cctbx open source library (Grosse-Kunstleve & Adams, 2002; Grosse-Kunstleve et al., 2002) to construct a standard refinement protocol, very much like phenix.refine and most other PHENIX tools. cctbx is used to compute the data term in (1) and its derivatives, perform scaling and…”