11 citations · 11 across the 2 of their papers we have counts for
5 papers
Incorporating Biological Knowledge with Factor Graph Neural Network for Interpretable Deep Learning
Tianle Ma, Aidong Zhang
While deep learning has achieved great success in many fields, one common criticism about deep learning is its lack of interpretability. In most cases, the hidden units in a deep n…
Multi-view Factorization AutoEncoder with Network Constraints for Multi-omic Integrative Analysis
Tianle Ma, Aidong Zhang
Multi-omic data provides multiple views of the same patients. Integrative analysis of multi-omic data is crucial to elucidate the molecular underpinning of disease etiology. Howeve…
Affinity Network Fusion and Semi-supervised Learning for Cancer Patient Clustering
Tianle Ma, Aidong Zhang
Defining subtypes of complex diseases such as cancer and stratifying patient groups with the same disease but different subtypes for targeted treatments is important for personaliz…
AffinityNet: semi-supervised few-shot learning for disease type prediction
Tianle Ma, Aidong Zhang
While deep learning has achieved great success in computer vision and many other fields, currently it does not work very well on patient genomic data with the "big p, small N" prob…
Integrate Multi-omic Data Using Affinity Network Fusion (ANF) for Cancer Patient Clustering
Tianle Ma, Aidong Zhang
Clustering cancer patients into subgroups and identifying cancer subtypes is an important task in cancer genomics. Clustering based on comprehensive multi-omic molecular profiling…