Using Graph Neural Networks to Predict Gene-Autoimmune Disease Associations

Links to Files

https://dl.acm.org/doi/abs/10.1145/3626203.3670603

Permanent Link

https://doi.org/10.1145/3626203.3670603
http://hdl.handle.net/11603/35253

Collections

UMBC Student Collection
UMBC Biological Sciences Department
UMBC Mathematics and Statistics Department

Author/Creator

Tomov, Stanimire

Date

Type of Work

conference papers and proceedings
Text

Citation of Original Publication

Dahle, Noah, Meghan Kwon, Kwai Wong, and Stanimire Tomov. “Using Graph Neural Networks to Predict Gene-Autoimmune Disease Associations.” In Practice and Experience in Advanced Research Computing 2024: Human Powered Computing, 1–4. PEARC ’24. New York, NY, USA: Association for Computing Machinery, 2024. https://doi.org/10.1145/3626203.3670603.

Subjects

MagmaDNN Framework
PyTorch Geometric
Gene-Autoimmune Disease
Graph neural networks (GNNs)
Heterogeneous Graphs
ChebNet (Chebyshev Networks)
Graph Convolutional Networks (GCNs)
Autoimmune Disorders
Drug Discovery