| HyperFoods: Machine intelligent mapping of cancer-beating molecules in foods K Veselkov, G Gonzalez, S Aljifri, D Galea, R Mirnezami, J Youssef, ... Scientific reports 9 (1), 9237, 2019 | 78 | 2019 |
| Network machine learning maps phytochemically rich “Hyperfoods” to fight COVID-19 I Laponogov, G Gonzalez, M Shepherd, A Qureshi, D Veselkov, ... Human genomics 15, 1-11, 2021 | 28 | 2021 |
| Predicting anticancer hyperfoods with graph convolutional networks G Gonzalez, S Gong, I Laponogov, M Bronstein, K Veselkov Human Genomics 15 (1), 33, 2021 | 15 | 2021 |
| Unsupervised network embedding beyond homophily Z Zhong, G Gonzalez, D Grattarola, J Pang arXiv preprint arXiv:2203.10866, 2022 | 10 | 2022 |
| Phytochemically rich dietary components and the risk of colorectal cancer: a systematic review and meta-analysis of observational studies P Borgas, G Gonzalez, K Veselkov, R Mirnezami World Journal of Clinical Oncology 12 (6), 482, 2021 | 10 | 2021 |
| Alzheimer’s disease: using gene/protein network machine learning for molecule discovery in olive oil L Rita, NR Neumann, I Laponogov, G Gonzalez, D Veselkov, D Pratico, ... Human Genomics 17 (57), 2023 | 8 | 2023 |
| Towards Training GNNs using Explanation Directed Message Passing V Giunchiglia, CV Shukla, G Gonzalez, C Agarwal Learning on Graphs Conference, 2022 | 7 | 2022 |
| On knowing a gene: A distributional hypothesis of gene function JJ Kwon, J Pan, G Gonzalez, WC Hahn, M Zitnik Cell Systems, 2024 | 5 | 2024 |
| Combinatorial prediction of therapeutic perturbations using causally-inspired neural networks G Gonzalez, I Herath, K Veselkov, M Bronstein, M Zitnik biorxiv, 2024 | 5 | 2024 |
| Unsupervised Heterophilous Network Embedding via г-Ego Network Discrimination Z Zhong, G Gonzalez, D Grattarola, J Pang | 4 | 2022 |
| Graph attentional autoencoder for anticancer hyperfood prediction G Gonzalez, S Gong, I Laponogov, K Veselkov, M Bronstein arXiv preprint arXiv:2001.05724, 2020 | 4 | 2020 |
| Crosstalk with lung fibroblasts shapes the growth and therapeutic response of mesothelioma cells Y Chrisochoidou, R Roy, P Farahmand, G Gonzalez, J Doig, L Krasny, ... Cell Death & Disease 14, 2023 | 3 | 2023 |
| Learning interpretable disease self-representations for drug repositioning F Frasca, D Galeano, G Gonzalez, I Laponogov, K Veselkov, A Paccanaro, ... arXiv preprint arXiv:1909.06609, 2019 | 3 | 2019 |
| Genomic-driven nutritional interventions for radiotherapy-resistant rectal cancer patient J Southern, G Gonzalez, P Borgas, L Poynter, I Laponogov, Y Zhong, ... Scientific Reports 13 (1), 14862, 2023 | 1 | 2023 |
| Expanding Genomic Discovery: Causally-Inspired Neural Networks for Predicting Therapeutic Targets G Gonzalez, I Herath, K Veselkov, MM Bronstein, M Zitnik ICLR 2024 Workshop on Machine Learning for Genomics Explorations, 2024 | | 2024 |
| Dietary components and the risk of colorectal cancer: A systematic review and meta-analysis of observational studies P Borgas, G Gonzalez, K Veselkov, R Mirnezami European Journal of Surgical Oncology 47 (2), e49, 2021 | | 2021 |
| Meta-analysis of the association between consumption of specific dietary components and risk of colorectal cancer P Borgas, G Gonzalez, K Veselkov, R Mirnezami European Journal of Surgical Oncology 47 (1), e5-e6, 2021 | | 2021 |
| Can foods help us fight COVID-19? The answer might be yes: Machine-learning-based techniques identify bioactive molecules in foods with antiviral properties G Gonzalez | | |
