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The causation of cancer often involves the joint deregulation of multiple biological processes. Thus, it is interesting to extract multi-function features of cancer genes and study their functional coordination involved in tumorigenesis. Here, based on Gene Ontology, we proposed a heuristics strategy to extract multi-function features which are significantly overrepresented with cancer genes. We showed...
The functional knowledge of cancer proteins and cancer pathways is currently limited and not detailed enough, remaining as a major hurdle to cancer studies. Particularly, many cancer proteins are only annotated to high-level general GO categories. Here, we apply an efficient algorithm, by constructing function-specific protein-protein interaction sub-networks, to find finer functions of the cancer...
Selecting differentially expressed genes (DEGs) is one of the most important tasks in microarray applications. However, the sample sizes typically used in current cancer studies may only partially reflect the widely altered gene expressions in cancers. By analyzing three large cancer datasets, we show that, in each cancer, a wide range of functional modules are altered and have high disease classification...
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