Difference between revisions of "MCL"
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The MCL algorithm is short for the Markov Cluster Algorithm, a fast and scalable unsupervised cluster algorithm for networks (also known as graphs) based on simulation of (stochastic) flow in graphs. The algorithm was invented/discovered by Stijn van Dongen (that is, me) at the Centre for Mathematics and Computer Science (also known as CWI) in the Netherlands. The PhD thesis Graph clustering by flow simulation is centered around this algorithm, the main topics being the mathematical theory behind it, its position in cluster analysis and graph clustering, issues concerning scalability, implementation, and benchmarking, and performance criteria for graph clustering in general. The work for this thesis was carried out under supervision of Jan van Eijck and Michiel Hazewinkel. | The MCL algorithm is short for the Markov Cluster Algorithm, a fast and scalable unsupervised cluster algorithm for networks (also known as graphs) based on simulation of (stochastic) flow in graphs. The algorithm was invented/discovered by Stijn van Dongen (that is, me) at the Centre for Mathematics and Computer Science (also known as CWI) in the Netherlands. The PhD thesis Graph clustering by flow simulation is centered around this algorithm, the main topics being the mathematical theory behind it, its position in cluster analysis and graph clustering, issues concerning scalability, implementation, and benchmarking, and performance criteria for graph clustering in general. The work for this thesis was carried out under supervision of Jan van Eijck and Michiel Hazewinkel. | ||
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Revision as of 02:41, 10 August 2012
Description
The MCL algorithm is short for the Markov Cluster Algorithm, a fast and scalable unsupervised cluster algorithm for networks (also known as graphs) based on simulation of (stochastic) flow in graphs. The algorithm was invented/discovered by Stijn van Dongen (that is, me) at the Centre for Mathematics and Computer Science (also known as CWI) in the Netherlands. The PhD thesis Graph clustering by flow simulation is centered around this algorithm, the main topics being the mathematical theory behind it, its position in cluster analysis and graph clustering, issues concerning scalability, implementation, and benchmarking, and performance criteria for graph clustering in general. The work for this thesis was carried out under supervision of Jan van Eijck and Michiel Hazewinkel.
Execution Environment and Modules
To use mcl with the environment modules system at HPC the following commands are available:
Get module information for mcl:
$module spider mcl
Load the default application module:
$module load mcl
The modulefile for this software adds the directory with executable files to the shell execution PATH and sets the following environment variables:
- HPC_MCL_DIR - directory where mcl is located.
- HPC_MCL_* HPC_MCL_BIN - executable directory
- HPC_MCL_DOC - documentation directory
- HPC_MCL_MAN - manpage directory