victor-gil-sepulveda/pyProCT
pyProCT is an open source cluster analysis software especially adapted for jobs related with structural proteomics. Its approach allows users to define a clustering goal (clustering hypothesis) based on their domain knowledge. This hypothesis will guide the software in order to find the best algorithm and parameters (including the number of clusters) to obtain the result that fulfills their expectatives. In this way users do not need to use cluster analysis algorithms as a black box, improving this way the results. pyProCT not only generates a resulting clustering, it also implements some use cases like the extraction of representatives or trajectory redundance elimination.
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