Describe the usefulness of CAMUR in The Cancer Genome Atlas (TCGA)
['CAMUR: Knowledge extraction from RNA-seq cancer data through equivalent classification rules', 'CAMUR, a new method that extracts multiple and equivalent classification models. CAMUR iteratively computes a rule-based classification model, calculates the power set of the genes present in the rules, iteratively eliminates those combinations from the data set, and performs again the classification procedure until a stopping criterion is verified. CAMUR includes an ad-hoc knowledge repository (database) and a querying tool.We analyze three different types of RNA-seq data sets (Breast, Head and Neck, and Stomach Cancer) from The Cancer Genome Atlas (TCGA) and we validate CAMUR and its models also on non-TCGA data. Our experimental results show the efficacy of CAMUR: we obtain several reliable equivalent classification models, from which the most frequent genes, their relationships, and the relation with a particular cancer are deduced', 'CAMUR includes an ad-hoc knowledge repository (database) and a querying tool.We analyze three different types of RNA-seq data sets (Breast, Head and Neck, and Stomach Cancer) from The Cancer Genome Atlas (TCGA) and we validate CAMUR and its models also on non-TCGA data.', 'CAMUR: Knowledge extraction from RNA-seq cancer data through equivalent classification rules.', 'We propose CAMUR, a new method that extracts multiple and equivalent classification models.']
['CAMUR is a new method that extracts multiple and equivalent classification models. CAMUR iteratively computes a rule-based classification model, calculates the power set of the genes present in the rules, iteratively eliminates those combinations from the data set, and performs again the classification procedure until a stopping criterion is verified. CAMUR includes an ad-hoc knowledge repository (database) and a querying tool. Three different types of RNA-seq data sets (Breast, Head and Neck, and Stomach Cancer) were analyzed from The Cancer Genome Atlas (TCGA) and CAMUR and its models were validated also on non-TCGA data. Experimental results show the efficacy of CAMUR by obtaining several reliable equivalent classification models, from which the most frequent genes, their relationships, and the relation with a particular cancer are deduced.']
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