Mean of Circular Quantities (MCQ) is a dissimilarity measure useful in comparison of 3D protein and/or RNA structures. It calculates an average difference between corresponding torsion angle values (rotations around bonds). More information can be found in:
Zok, T., Popenda, M., & Szachniuk, M. (2014). MCQ4Structures to compute similarity of molecule structures. Central European Journal of Operations Research, 22(3), 457โ473. https://doi.org/10.1007/s10100-013-0296-5
git clone https://github.com/tzok/mcq4structures.git
cd mcq4structures
mvn install
This project consists of a few subprojets:
mcq-common
: base functionalitymcq-clustering
: partitional and hierarchical clusteringmcq-cli
: command-line interfacemcq-gui
: graphical interface
- Use
pl.poznan.put.comparison.MCQ#compareGlobally
to compare two 3D structures and obtain a global value of dissimilarity. You can usepl.poznan.put.comparison.global.ParallelGlobalComparator
to process multiple inputs in parallel - Use
pl.poznan.put.comparison.MCQ#comparePair
to obtain detailed information about dissimilarity of two 3D structures - Use
pl.poznan.put.comparison.MCQ#compareModels
in a situation where a distinguished reference 3D structure is known and you want to know how 3D models compare to it
- Use
pl.poznan.put.clustering.hierarchical.Clusterer
to construct dendrograms from a distance matrix (withCOMPLETE
,SINGLE
orAVERAGE
linkage option) - Use
pl.poznan.put.clustering.partitional.KMedoids
to perform partitional clustering based on distance matrix - Use
pl.poznan.put.clustering.partitional.KScanner#parallelScan
to find optimum number of clusters with respect to silhouette score