Background: Theme-driven cancer survival studies address whether the expression signature of genes related to a biological process can predict patient survival time. Although this...
Background: High-throughput automated sequencing has enabled an exponential growth rate of sequencing data. This requires increasing sequence quality and reliability in order to a...
Background: In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput t...
Background: Recent advances in proteomics technologies such as SELDI-TOF mass spectrometry has shown promise in the detection of early stage cancers. However, dimensionality reduc...
Kai-Lin Tang, Tong-Hua Li, Wen-Wei Xiong, Kai Chen
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...