Mingguang Shi

发表

Semi-supervised learning improves gene expression-based prediction of cancer recurrence

Bing Zhang, Mingguang Shi, Mingguang Shi, 2011, Bioinform..

A Network-Based Gene Expression Signature Informs Prognosis and Treatment for Colorectal Cancer Patients

Mingguang Shi, Bing Zhang, R. Beauchamp, 2012, PloS one.

Network-based sub-network signatures unveil the potential for acute myeloid leukemia therapy.

Mingguang Shi, Min Wu, P. Pan, 2014, Molecular bioSystems.

SNRFCB: sub-network based random forest classifier for predicting chemotherapy benefit on survival for cancer treatment.

Mingguang Shi, Jianmin He, 2016, Molecular bioSystems.

Development and validation of GMI signature based random survival forest prognosis model to predict clinical outcome in acute myeloid leukemia

Mingguang Shi, Guofu Xu, 2019, BMC Medical Genomics.

ColoFinder: a prognostic 9-gene signature improves prognosis for 871 stage II and III colorectal cancer patients

Mingguang Shi, Jianmin He, 2016, PeerJ.

Spectral clustering using Nyström approximation for the accurate identification of cancer molecular subtypes

Mingguang Shi, Guofu Xu, 2017, Scientific Reports.

Integration of Cancer Genomics Data for Tree‐based Dimensionality Reduction and Cancer Outcome Prediction

Chenyu Zhang, Mingguang Shi, Junwen Wang, 2019, Molecular informatics.

Development and validation of GMI signature based random survival forest prognosis model to predict clinical outcome in acute myeloid leukemia

Mingguang Shi, Guofu Xu, 2019, BMC Medical Genomics.

Prognostic outcome prediction by semi-supervised least squares classification

Hao Tang, Zhou Sheng, Mingguang Shi, 2020, Briefings Bioinform..

Spectral clustering using Nyström approximation for the accurate identification of cancer molecular subtypes

Mingguang Shi, Guofu Xu, Mingguang Shi, 2017, Scientific Reports.