BiC2PAM (BiClustering with Constraints using PAttern Mining) is a biclustering algorithm for unsupervised data analysis with domain knowledge.
BiC2PAM integrates recent breakthroughs on pattern-based biclustering (including BicPAM, BicNET and BicSPAM algorithms) and extends them to effectively incorporate constraints and annotations. In this context, the underlying pattern mining searches are: adapted to learn from data with annotations derived from knowledge repositories, and enhanced to be able to explore efficiency gains from constraints with succinct, (anti-)monotone and convertible properties.

Authors: Rui Henriques and Sara Madeira
Please cite: contributions currently under review, contact Rui Henriques,, to obtain the updated reference.

Synthetic datasets (non-exhaustive set):

Real datasets:

Results: statistical sheets and biological analyses