Discovering Pair-wise Synergies in Microarray Data

Discovering Pair-wise Synergies in Microarray Data

Informative gene selection can have important implications for the improvement of cancer diagnosis and the identification of new drug targets. Individual-gene-ranking methods ignore interactions between genes. Furthermore, popular pair-wise gene evaluation methods, e.g. TSP and TSG, are helpless for discovering pair-wise interactions. Several efforts to discover pair-wise synergy have been made...

Discovering Pair-Wise Genetic Interactions: An Information Theory-Based Approach

Phenotypic variation, including that which underlies health and disease in humans, results in part from multiple interactions among both genetic variation and environmental factors. While diseases or phenotypes caused by single gene variants can be identified by established association methods and family-based approaches, complex phenotypic traits resulting from multi-gene interactions remain v...

cDNA Microarray Data Normalization

Pair-Wise Privilege Control for Cross-Domain Private Data Sharing

Enterprise-scale organizations have large numbers of internal and external users, with different privilege requirements spanning across many resources. The dynamic nature of modern organizations demands that they efficiently and securely provision and deactivate data privileges to reflect rapidly changing user responsibilities. Previous approaches to consolidated user provisioning have focused ...

Fundamental Properties of Pair - Wise

In traditional mechanics, most interactions are pair-wise; if we omit one of the particles from our description, then the original pair-wise interaction can sometimes only be represented as interaction between triples, etc. It turns out that, vice versa, every possible interaction between N particles can be represented as pair-wise interaction if we represent each of the original N particles as...