12 citations · 47 across the 9 of their papers we have counts for
11 papers
Biomarker-guided heterogeneity analysis of genetic regulations via multivariate sparse fusion
Sanguo Zhang, Xiaonan Hu, Ziye Luo +3
Heterogeneity is a hallmark of many complex diseases. There are multiple ways of defining heterogeneity, among which the heterogeneity in genetic regulations, for example GEs (gene…
An integrative sparse boosting analysis of cancer genomic commonality and difference
Yifan Sun, Zhengyang Sun, Yu Jiang +2
In cancer research, high-throughput profiling has been extensively conducted. In recent studies, the integrative analysis of data on multiple cancer patient groups/subgroups has be…
Identification of cancer omics commonality and difference via community fusion
Yifan Sun, Yu Jiang, Yang Li +1
The analysis of cancer omics data is a "classic" problem, however, still remains challenging. Advancing from early studies that are mostly focused on a single type of cancer, some…
Robust structured heterogeneity analysis approach for high-dimensional data
Yifan Sun, Ziye Luo, Xinyan Fan
Revealing relationships between genes and disease phenotypes is a critical problem in biomedical studies. This problem has been challenged by the heterogeneity of diseases. Patient…
Robust nonparametric integrative analysis to decipher heterogeneity and commonality across subgroups using sparse boosting
Zihan Li, Ziye Luo, Yifan Sun
In many biomedical problems, data are often heterogeneous, with samples spanning multiple patient subgroups, where different subgroups may have different disease subtypes, stages,…
Semiparametric integrative interaction analysis for non-small-cell lung cancer
Yang Li, Fan Wang, Rong Li +1
In the genomic analysis, it is significant while challenging to identify markers associated with cancer outcomes or phenotypes. Based on the biological mechanisms of cancers and th…