Consists as an deterministic graph-based method that is designed to find maximal constant-column biclusters in any given data matrix. GRAph-based Constant-cOlumn Biclustering (Gracob) is developed to discover co-fit genes from large growth phenotype profiling data sets. It takes advantage of the sparsity of biclusters and compared to the size of the input data matrix, the number of biclusters in the matrix is small. Gracob consists of three main phases: 1) the pre-processing phase, 2) the graph creation phase, and 3) the maximal clique finding phase.
King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Thuwal, Saudi Arabia; Department of Computer Science, University of California, Los Angeles, Boelter Hall, Los Angeles, CA, USA.
Gracob funding source(s)
This work was supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. URF/1/1976-04.