BiP is an algorithm that learns flexible plaid models for an effective discovery of overlapping biclusters.
BiP addresses the limitations of existing plaid models, namely overcomes existing restrictions on the allowed types and structures of biclusters.
BiP makes available different functions to compose contributions from overlapping biclusters, such as weighted and multiplicative functions.
BiP allows the use of different relaxation for noise-tolerant and biologically-meaningful validation of plaid effects.

Authors: Rui Henriques and Sara Madeira
	title={Biclustering with Flexible Plaid Models to Unravel Interactions between Biological Processes}, 
	journal={Computational Biology and Bioinformatics, IEEE/ACM Transactions on}, 
	author={Henriques, R. and Madeira, S.}, 
	volume={}, //to appear 
	number={}, //to appear
	pages={}, //to appear

Synthetic datasets (non-exhaustive set of 6 data instances with background values following Uniform and Normal distributions):

Real datasets:

Results: Statistical Sheets of BiP (using alternative biclustering solutions) and BCPlaid