Determination of disease related biological processes and the estimation of molecular interactions related to these processes are important to understand the underlying mechanism of diseases. In our study we infer gene co-expression networks of breast and colon cancer using miRNA-target gene interactions. Popular information theory based gene network inference algorithms are utilized to infer gene co-expression networks. Literature data, which is used as validation data in overlap analysis, is used to measure the performances of gene network inference algorithms. According to the results, the precision values of gene co-expression networks of two cancers are close to each other. Our study also states that the relevance calculation methods of gene-gene interactions at the first step of gene network inference algorithms don't change the performance results of gene co-expression networks.