21 citations · 34 across the 7 of their papers we have counts for
7 papers
PerturbRx: Learning Treatment-Conditioned Latent Transitions for Patient Drug Response Prediction
Yoshitaka Inoue, Minoh Jeong, Alfred Hero +2
Scarce data and tumor heterogeneity limit patient-level cancer treatment-response prediction. Existing approaches predict response from pretreatment molecular profiles and drug rep…
DrugAgent: Reliable Multi-Agent Integration of Conflicting Biomedical Evidence for Drug-Target Interaction Assessment
Yoshitaka Inoue, Tianci Song, Xinling Wang +3
Workflows in drug-target interaction (DTI) assessment require integrating heterogeneous data from predictive models, curated resources, and observations from experimental literatur…
Scalable Label Propagation for Multi-relational Learning on the Tensor Product of Graphs
Zhuliu Li, Raphael Petegrosso, Shaden Smith +3
Multi-relational learning on knowledge graphs infers high-order relations among the entities across the graphs. This learning task can be solved by label propagation on the tensor…
Low-rank Label Propagation for Semi-supervised Learning with 100 Millions Samples
Raphael Petegrosso, Wei Zhang, Zhuliu Li +2
The success of semi-supervised learning crucially relies on the scalability to a huge amount of unlabelled data that are needed to capture the underlying manifold structure for bet…
Predicting Small Group Accretion in Social Networks: A topology based incremental approach
Ankit Sharma, Xiaodong Feng, Kartik Singhal +2
Small Group evolution has been of central importance in social sciences and also in the industry for understanding dynamics of team formation. While most of research works studying…
Network-based Isoform Quantification with RNA-Seq Data for Cancer Transcriptome Analysis
Wei Zhang, Jae-Woong Chang, Lilong Lin +6
High-throughput mRNA sequencing (RNA-Seq) is widely used for transcript quantification of gene isoforms. Since RNA-Seq data alone is often not sufficient to accurately identify the…
Inferring Disease and Gene Set Associations with Rank Coherence in Networks
TaeHyun Hwang, Wei Zhang, Maoqiang Xie +1
A computational challenge to validate the candidate disease genes identified in a high-throughput genomic study is to elucidate the associations between the set of candidate genes…