5 citations · 5 across the 3 of their papers we have counts for
5 papers
Network-principled deep generative models for designing drug combinations as graph sets
Mostafa Karimi, Arman Hasanzadeh, Yang shen
Combination therapy has shown to improve therapeutic efficacy while reducing side effects. Importantly, it has become an indispensable strategy to overcome resistance in antibiotic…
Directionally Dependent Multi-View Clustering Using Copula Model
Kahkashan Afrin, Ashif S. Iquebal, Mostafa Karimi +3
In recent biomedical scientific problems, it is a fundamental issue to integratively cluster a set of objects from multiple sources of datasets. Such problems are mostly encountere…
Explainable Deep Relational Networks for Predicting Compound-Protein Affinities and Contacts
Mostafa Karimi, Di Wu, Zhangyang Wang +1
Predicting compound-protein affinity is critical for accelerating drug discovery. Recent progress made by machine learning focuses on accuracy but leaves much to be desired for int…
Illegible Text to Readable Text: An Image-to-Image Transformation using Conditional Sliced Wasserstein Adversarial Networks
Mostafa Karimi, Gopalkrishna Veni, Yen-Yun Yu
Automatic text recognition from ancient handwritten record images is an important problem in the genealogy domain. However, critical challenges such as varying noise conditions, va…
DeepAffinity: Interpretable Deep Learning of Compound-Protein Affinity through Unified Recurrent and Convolutional Neural Networks
Mostafa Karimi, Di Wu, Zhangyang Wang +1
Motivation: Drug discovery demands rapid quantification of compound-protein interaction (CPI). However, there is a lack of methods that can predict compound-protein affinity from s…