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- W2106927844 abstract "This paper proposes a novel modeling technique for understanding cancer signal pathway and applies to cancer classification. In the approach, specific to a cancer group, a regulatory network is constructed between biomarkers and is optimized towards minimizing its energy function that is defined as disagreement between input and output of the network. The non-linear version of this network is achieved by imposing a sigmoid kernel function. The proposed approach is tested on protein profiling data of nasopharyngeal carcinoma and is compared with support vector machines with linear and radial basis function kernels." @default.
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- W2106927844 date "2008-05-01" @default.
- W2106927844 modified "2023-10-07" @default.
- W2106927844 title "Exploring Protein Regulations with Regulatory Networks for Cancer Classification" @default.
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- W2106927844 doi "https://doi.org/10.1109/bmei.2008.205" @default.
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