14 citations · 27 across the 5 of their papers we have counts for
5 papers
Mathematical deep learning for pose and binding affinity prediction and ranking in D3R Grand Challenges
Duc Duy Nguyen, Zixuan Cang, Kedi Wu +3
Advanced mathematics, such as multiscale weighted colored graph and element specific persistent homology, and machine learning including deep neural networks were integrated to con…
TopP-S: Persistent homology based multi-task deep neural networks for simultaneous predictions of partition coefficient and aqueous solubility
Kedi Wu, Zhixiong Zhao, Renxiao Wang +1
Aqueous solubility and partition coefficient are important physical properties of small molecules. Accurate theoretical prediction of aqueous solubility and partition coefficient p…
Quantitative toxicity prediction using topology based multi-task deep neural networks
Kedi Wu, Guo-Wei Wei
The understanding of toxicity is of paramount importance to human health and environmental protection. Quantitative toxicity analysis has become a new standard in the field. This w…
Comparison of multi-task convolutional neural network (MT-CNN) and a few other methods for toxicity prediction
Kedi Wu, Guo-Wei Wei
Toxicity analysis and prediction are of paramount importance to human health and environmental protection. Existing computational methods are built from a wide variety of descripto…
A topological approach for protein classification
Zixuan Cang, Lin Mu, Kedi Wu +3
Protein function and dynamics are closely related to its sequence and structure. However prediction of protein function and dynamics from its sequence and structure is still a fund…