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Proceedings of the ACM fourth international workshop on Data and text mining in biomedical informatics - DTMBIO '10
Breast cancer is a highly heterogeneous disease with respect to molecular alterations and cellular composition making therapeutic and clinical outcome unpredictable. This diversity creates a significant challenge in developing tumor classifications that are clinically reliable with respect to prognosis prediction. Results: This paper describes an unsupervised context analysis to infer context-specific gene regulatory networks from 1,614 samples obtained from publicly available gene expressiondoi:10.1145/1871871.1871875 fatcat:rj4swxhc7fhlxpv7bao2qwicue