Abstract: The present invention relates compositions and methods for microRNA (miRNA) expression profiling of colorectal cancer. In particular, the invention relates to a diagnostic kit of molecular markers for identifying one or more mammalian target cells exhibiting or having a predisposition to develop colorectal cancer, the kit comprising a plurality of nucleic acid molecules, each nucleic acid molecule encoding a miRNA sequence, wherein one or more of the plurality of nucleic acid molecules are differentially expressed in the target cells and in one or more control cells, and wherein the one or more differentially expressed nucleic acid molecules together represent a nucleic acid expression signature that is indicative for the presence of or the predisposition to develop colorectal cancer.

Abstract: This invention relates to a method and an apparatus for determining a reliability indicator for at least one set of signatures obtained from clinical data collected from a group of samples. The signatures are obtained by detecting characteristics in the clinical data from the group of sample sand each of the signatures generate a first set of stratification values that stratify the group of samples. At least one additional and parallel stratification source to the signatures obtained from group of sample sis provided, the at least one additional and parallel stratification source to the signatures being independent from the signatures and generates a second set of stratification values. A comparison is done for each respective sample, where the first stratification values are compared with a true reference stratification values, and where the second stratification values are compared with the true reference stratification values.

Abstract: The present invention relates to effective diagnosis of patients and assisting clinicians in treatment planning. In particular, invention provides a medical analysis system that enables refinement of molecular classification. The system provides a molecular profiling solution that will allow improved diagnosis, prognosis, response prediction to provide the right chemotherapy, and follow-up to monitor for cancer recurrence.

Abstract: Systems and methods for selecting factors from a data set of measurements are provided. The measurements include values of factors and/or outcomes. Two or more factors that are jointly associated with one or more outcomes from the data set are identified. Each of the two or more factors are analyzed to determine at least one cooperative interaction among the factors with respect to an outcome. The two or more factors can be a module of factors.

Abstract: The disclosed subject matter provides techniques for multiple-factor selection. The factors can be features or elements that are jointly associated with one or more outcomes by their joint presence or absence. There may be a non-causative correlation between the factors, features, or elements and the outcomes. In some embodiments, Entropy Minimization and Boolean Parsimony (EMBP) is used to identify modules of genes jointly associated with disease from gene expression data, and a logic function is provided to connect the combined expression levels in each gene module with the presence of disease. The smallest module of genes whose joint expression levels can predict the presence of disease can be identified.