Xiaodong Cai

This paper introduces SSEMQ, a method that jointly maps eQTLs and infers gene regulatory networks, improving detection power for both cis- and trans-eQTLs.

This study introduces ExpResNet, a deep residual network for predicting gene expression from DNA sequence, showing improved performance over existing models on GTEx data.

The paper introduces FSSEM, a method to jointly infer gene regulatory networks under two conditions and identify differential networks, showing improved accuracy over separate inference approaches.

This paper introduces ProGAdNet, a proximal gradient algorithm for joint inference of differential gene networks, showing improved accuracy and speed over existing methods in identifying network changes in breast cancer data.