| Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions A Culos, AS Tsai, N Stanley, M Becker, MS Ghaemi, DR McIlwain, ... Nature machine intelligence 2 (10), 619-628, 2020 | 67 | 2020 |
| Low rank spectral network alignment H Nassar, N Veldt, S Mohammadi, A Grama, DF Gleich Proceedings of the 2018 World Wide Web Conference, 619-628, 2018 | 56 | 2018 |
| VoPo leverages cellular heterogeneity for predictive modeling of single-cell data N Stanley, IA Stelzer, AS Tsai, R Fallahzadeh, E Ganio, M Becker, ... Nature communications 11 (1), 3738, 2020 | 46 | 2020 |
| Julia for biologists E Roesch, JG Greener, AL MacLean, H Nassar, C Rackauckas, TE Holy, ... Nature methods 20 (5), 655-664, 2023 | 44 | 2023 |
| Early prediction and longitudinal modeling of preeclampsia from multiomics I Marić, K Contrepois, MN Moufarrej, IA Stelzer, D Feyaerts, X Han, ... Patterns 3 (12), 2022 | 27 | 2022 |
| Neighborhood and PageRank methods for pairwise link prediction H Nassar, AR Benson, DF Gleich Social Network Analysis and Mining 10, 1-13, 2020 | 26 | 2020 |
| Pairwise link prediction H Nassar, AR Benson, DF Gleich Proceedings of the 2019 IEEE/ACM International Conference on Advances in …, 2019 | 25 | 2019 |
| Strong localization in personalized PageRank vectors H Nassar, K Kloster, DF Gleich Algorithms and Models for the Web Graph: 12th International Workshop, WAW …, 2015 | 22 | 2015 |
| Multimodal network diffusion predicts future disease–gene–chemical associations CH Lin, DM Konecki, M Liu, SJ Wilson, H Nassar, AD Wilkins, DF Gleich, ... Bioinformatics 35 (9), 1536-1543, 2019 | 20 | 2019 |
| Multimodal network alignment H Nassar, DF Gleich Proceedings of the 2017 SIAM International Conference on Data Mining, 615-623, 2017 | 18 | 2017 |
| Large-scale correlation network construction for unraveling the coordination of complex biological systems M Becker, H Nassar, C Espinosa, IA Stelzer, D Feyaerts, E Berson, ... Nature computational science 3 (4), 346-359, 2023 | 14 | 2023 |
| Rigid graph alignment V Ravindra, H Nassar, DF Gleich, A Grama Complex Networks and Their Applications VIII: Volume 1 Proceedings of the …, 2020 | 11 | 2020 |
| Using cliques with higher-order spectral embeddings improves graph visualizations H Nassar, C Kennedy, S Jain, AR Benson, D Gleich Proceedings of The Web Conference 2020, 2927-2933, 2020 | 7 | 2020 |
| A longitudinal study of the post-stroke immune response and cognitive functioning: the StrokeCog study protocol LL Drag, M Mlynash, H Nassar, E Osborn, DE Kim, MS Angst, ... BMC neurology 20, 1-7, 2020 | 5 | 2020 |
| Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions. Nat. Mach. Intell. 2, 619–628 A Culos, AS Tsai, N Stanley, M Becker, MS Ghaemi, DR McIlwain, ... Crossref, Medline, 2020 | 5 | 2020 |
| Localization in seeded pagerank DF Gleich, K Kloster, H Nassar arXiv preprint arXiv:1509.00016, 2015 | 4 | 2015 |
| Aligning spatially constrained graphs V Ravindra, H Nassar, DF Gleich, A Grama IEEE Transactions on Knowledge and Data Engineering 35 (8), 7712-7723, 2022 | 3 | 2022 |
| Multiomics Longitudinal Modeling of Preeclamptic Pregnancies I Maric, K Contrepois, M Moufarrej, I Stelzer, D Feyaerts, X Han, A Tang, ... | 3 | 2021 |
| Dominant Z-Eigenpairs of Tensor Kronecker Products Decouple C Colley, H Nassar, DF Gleich SIAM Journal on Matrix Analysis and Applications 44 (3), 1006-1031, 2023 | 2 | 2023 |
| Machine learning models of plasma proteomic data predict mood in chronic stroke and tie it to aberrant peripheral immune responses NH Bidoki, KA Zera, H Nassar, LL Drag, M Mlynash, E Osborn, ... Brain, Behavior, and Immunity 114, 144-153, 2023 | 1 | 2023 |
