Clustering Methods

The current version of ArchDB (ArchDB14) includes two different methods of loop clustering. This is intended to provide the ArchDB user with as much usability as possible. (Learn more...)
The Density Search (DS) algorithm detects regions with a high density of loops in a features space defined by the length, bracing secondary structures, conformation and geometry of the loops. (Learn more...)
The Markov CLusetering (MCL) algorithm is a graph-based clustering algorithm that simulates a flow of information within the graph, enhancing the flow where the curretn is strong and hindering where the current is weak. (Learn more...)
Overlap between the different classification methods
TypeDSDS and MCLMCL
BK66990527341
BN664292835176
EG37091913466
EH7591796111442
GE25288763078
GG18861712
GH7196683074
HE4071923812226
HG5875313707
HH1881416311071

Radar plot showing the proportion of different types of loops extracted from known protein structures that have been classified by each clustering method.

Each radial axis of the plot corresponds to one type of loop (i.e. loops with the same type of bracing secondary structures). The different types of loops are defined in the database main page.

The vertices of each colored polygon denote the the number of classified loops according to their type.

The colors of the polygons represent the clustering methods:

  • In blue, loops only classified by Density Search;
  • In yellow, loops only classified by Markov CLustering;
  • In green, loops classified by both methods.

Note that polygons are stacked: the total number of loops classified by Density Search is the sum of blue and green areas; the total number of loops classified by Markov CLustering is the sum of green and yellow areas.