16 citations · 35 across the 4 of their papers we have counts for
12 papers
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development
Kexin Huang, Tianfan Fu, Wenhao Gao +7
Therapeutics machine learning is an emerging field with incredible opportunities for innovatiaon and impact. However, advancement in this field requires formulation of meaningful l…
An Interpretable End-to-end Fine-tuning Approach for Long Clinical Text
Kexin Huang, Sankeerth Garapati, Alexander S. Rich
Unstructured clinical text in EHRs contains crucial information for applications including decision support, trial matching, and retrospective research. Recent work has applied BER…
MolDesigner: Interactive Design of Efficacious Drugs with Deep Learning
Kexin Huang, Tianfan Fu, Dawood Khan +7
The efficacy of a drug depends on its binding affinity to the therapeutic target and pharmacokinetics. Deep learning (DL) has demonstrated remarkable progress in predicting drug ef…
scGNN: scRNA-seq Dropout Imputation via Induced Hierarchical Cell Similarity Graph
Kexin Huang
Single-cell RNA sequencing provides tremendous insights to understand biological systems. However, the noise from dropout can corrupt the downstream biological analysis. Hence, it…
Graph Meta Learning via Local Subgraphs
Kexin Huang, Marinka Zitnik
Prevailing methods for graphs require abundant label and edge information for learning. When data for a new task are scarce, meta-learning can learn from prior experiences and form…
MolTrans: Molecular Interaction Transformer for Drug Target Interaction Prediction
Kexin Huang, Cao Xiao, Lucas Glass +1
Drug target interaction (DTI) prediction is a foundational task for in silico drug discovery, which is costly and time-consuming due to the need of experimental search over large d…