TRIQ: A Comprehensive Evaluation Measure for Triclustering Algorithms

Triclustering has shown to be a valuable tool for the analysis of microarray data since its appearance as an improvement of classical clustering and biclustering techniques. Triclustering relaxes the constraints for grouping and allows genes to be evaluated under a subset of experimental conditions and a subset of time points simultaneously. The authors previously presented a genetic algorithm, TriGen, that finds triclusters of gene expression dasta. They also defined three different fitness functions for TriGen: MSR3D, LSL and MSL. In order to asses the results obtained by application of TriGen, a validity measure needs to be defined. Therefore, we present TRIQ, a validity measure which combines information from three different sources: (1) correlation among genes, conditions and times, (2) graphic validation of the patterns extracted and (3) functional annotations for the genes extracted.Ministerio de Ciencia y Tecnología TIN2011-28956-C02-02Ministerio de ciencia y Tecnología TIN2014-55894-C2-1-RJunta de Andalucía P12-TIC-752

MSL: A Measure to Evaluate Three-dimensional Patterns in Gene Expression Data

Microarray technology is highly used in biological research environments due to its ability to monitor the RNA concentration levels. The analysis of the data generated represents a computational challenge due to the characteristics of these data. Clustering techniques are widely applied to create groups of genes that exhibit a similar behavior. Biclustering relaxes the constraints for grouping, allowing genes to be evaluated only under a subset of the conditions. Triclustering appears for the analysis of longitudinal experiments in which the genes are evaluated under certain conditions at several time points. These triclusters provide hidden information in the form of behavior patterns from temporal experiments with microarrays relating subsets of genes, experimental conditions, and time points. We present an evaluation measure for triclusters called Multi Slope Measure, based on the similarity among the angles of the slopes formed by each profile formed by the genes, conditions, and times of the triclusterMinisterio de Ciencia y Tecnología TIN2011-28956-C02-02Junta de Andalucía TIC-752