Our science 03
Publications
Peer-reviewed work and preprints from our team on binding prediction for novel targets, interaction modeling, and generalizable machine learning for drug discovery.
- 2026
Ravandi, C. B., Mowrey, W. R., Chatterjee, A., Khanshan, F., Haddadi, P., Mobarec, J. C., Lambden, S., Eliassi-Rad, T., Ricchiuto, P., & Risa, G. (2026). Clinical trial and ontology-derived positive and negative benchmark datasets for drug repurposing across rare diseases. bioRxiv , 2026.06.15.732135.
- 2025
Chatterjee, A., Ikica, B., Ravandi, B., & Palowitch, J. (2025). Transfer learning for temporal link prediction. 2025 International Joint Conference on Neural Networks (IJCNN) , 1–8.
- 2025
Chatterjee, A., Ravandi, B., Haddadi, P., Philip, N. H., Abdelmessih, M., Mowrey, W. R., Ricchiuto, P., Liang, Y., Ding, W., Mobarec, J. C., & Eliassi-Rad, T. (2025). Topology-driven negative sampling enhances generalizability in protein–protein interaction prediction. Bioinformatics, 41 (5), btaf148.
- 2024
Ravandi, B., Mowrey, W. R., Chatterjee, A., Haddadi, P., Abdelmessih, M., Ding, W., Lambden, S., Ughetto, M., Barrett, I., Diethe, T., Del Angel, G., Eliassi-Rad, T., & Ricchiuto, P. (2024). Representation learning of human disease mechanisms for a foundation model in rare and common diseases. bioRxiv , 2024.11.19.624381.
- 2024
Shafi, Z., Chatterjee, A., & Eliassi-Rad, T. (2024). Generating human understandable explanations for node embeddings. arXiv , 2406.07642.
- 2024
Sunil, S., Rajeev, R. S., Chatterjee, A., Pilitsis, J., Mukherjee, A., & Paluh, J. L. (2024). SIENNA: Lightweight generalizable machine learning platform for brain tumor diagnostics. medRxiv , 2024.04.03.24305210.
- 2023
Chatterjee, A., Walters, R., Shafi, Z., Ahmed, O. S., Sebek, M., Gysi, D., Yu, R., Eliassi-Rad, T., Barabási, A.-L., & Menichetti, G. (2023). Improving the generalizability of protein-ligand binding predictions with AI-Bind. Nature Communications, 14 (1), 1989.
- 2023
Chatterjee, A., Walters, R., Menichetti, G., & Eliassi-Rad, T. (2023). Inductive link prediction in static and temporal graphs for isolated nodes. Temporal Graph Learning Workshop @ NeurIPS 2023 .
- 2023
Chatterjee, A., Walters, R., Menichetti, G., & Eliassi-Rad, T. (2023). Disentangling node attributes from graph topology for improved generalizability in link prediction. arXiv , 2307.08877.
- 2023
Shafi, Z., Miller, B. A., Chatterjee, A., Eliassi-Rad, T., & Caceres, R. S. (2023). GRASP: Accelerating shortest path attacks via graph attention. arXiv , 2310.07980.
- 2022
Pacza, T., Martins, M. L., Rockaya, M., Müller, K., Chatterjee, A., Barabási, A.-L., & Baranyi, J. (2022). MilkyBase, a database of human milk composition as a function of maternal-, infant- and measurement conditions. Scientific Data, 9 , 557.