117 citations · 316 across the 5 of their papers we have counts for
5 papers
OmiTrans: generative adversarial networks based omics-to-omics translation framework
Xiaoyu Zhang, Yike Guo
With the rapid development of high-throughput experimental technologies, different types of omics (e.g., genomics, epigenomics, transcriptomics, proteomics, and metabolomics) data…
XOmiVAE: an interpretable deep learning model for cancer classification using high-dimensional omics data
Eloise Withnell, Xiaoyu Zhang, Kai Sun +1
The lack of explainability is one of the most prominent disadvantages of deep learning applications in omics. This "black box" problem can undermine the credibility and limit the p…
OmiEmbed: a unified multi-task deep learning framework for multi-omics data
Xiaoyu Zhang, Yuting Xing, Kai Sun +1
High-dimensional omics data contains intrinsic biomedical information that is crucial for personalised medicine. Nevertheless, it is challenging to capture them from the genome-wid…
Unsupervised Annotation of Phenotypic Abnormalities via Semantic Latent Representations on Electronic Health Records
Jingqing Zhang, Xiaoyu Zhang, Kai Sun +3
The extraction of phenotype information which is naturally contained in electronic health records (EHRs) has been found to be useful in various clinical informatics applications su…
Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification
Xiaoyu Zhang, Jingqing Zhang, Kai Sun +3
Different aspects of a clinical sample can be revealed by multiple types of omics data. Integrated analysis of multi-omics data provides a comprehensive view of patients, which has…