| A single cell transcriptomic atlas characterizes aging tissues in the mouse Tabula Muris Consortium Nature 583 (7817), 590, 2020 | 958 | 2020 |
| A human brain vascular atlas reveals diverse mediators of Alzheimer’s risk AC Yang, RT Vest, F Kern, DP Lee, M Agam, CA Maat, PM Losada, ... Nature 603 (7903), 885-892, 2022 | 588 | 2022 |
| Ageing hallmarks exhibit organ-specific temporal signatures N Schaum, B Lehallier, O Hahn, R Pálovics, S Hosseinzadeh, SE Lee, ... Nature 583 (7817), 596-602, 2020 | 485 | 2020 |
| Organ aging signatures in the plasma proteome track health and disease HSH Oh, J Rutledge, D Nachun, R Pálovics, O Abiose, P Moran-Losada, ... Nature 624 (7990), 164-172, 2023 | 218 | 2023 |
| Young CSF restores oligodendrogenesis and memory in aged mice via Fgf17 T Iram, F Kern, A Kaur, S Myneni, AR Morningstar, H Shin, MA Garcia, ... Nature 605 (7910), 509-515, 2022 | 166 | 2022 |
| APOE4/4 is linked to damaging lipid droplets in Alzheimer’s disease microglia MS Haney, R Pálovics, CN Munson, C Long, PK Johansson, O Yip, ... Nature 628 (8006), 154-161, 2024 | 145 | 2024 |
| Molecular hallmarks of heterochronic parabiosis at single-cell resolution R Pálovics, A Keller, N Schaum, W Tan, T Fehlmann, M Borja, F Kern, ... Nature 603 (7900), 309-314, 2022 | 100 | 2022 |
| Atlas of the aging mouse brain reveals white matter as vulnerable foci O Hahn, AG Foltz, M Atkins, B Kedir, P Moran-Losada, IH Guldner, ... Cell 186 (19), 4117-4133. e22, 2023 | 90 | 2023 |
| Exploiting temporal influence in online recommendation R Pálovics, AA Benczúr, L Kocsis, T Kiss, E Frigó Proceedings of the 8th ACM Conference on Recommender systems, 273-280, 2014 | 76 | 2014 |
| Recsys challenge 2016: Job recommendations F Abel, A Benczúr, D Kohlsdorf, M Larson, R Pálovics Proceedings of the 10th ACM Conference on Recommender Systems, 425-426, 2016 | 61 | 2016 |
| Online Machine Learning in Big Data Streams AA Benczúr, L Kocsis, R Pálovics arXiv preprint arXiv:1802.05872, 2018 | 56 | 2018 |
| Node embeddings in dynamic graphs F Béres, DM Kelen, R Pálovics, AA Benczúr Applied Network Science 4 (1), 64, 2019 | 41 | 2019 |
| Temporal influence over the Last. fm social network R Pálovics, AA Benczúr Social Network Analysis and Mining 5 (1), 4, 2015 | 39 | 2015 |
| Temporal walk based centrality metric for graph streams F Béres, R Pálovics, A Oláh, AA Benczúr Applied network science 3, 1-26, 2018 | 34 | 2018 |
| Location-aware online learning for top-k recommendation R Pálovics, P Szalai, J Pap, E Frigó, L Kocsis, AA Benczúr Pervasive and Mobile Computing 38, 490-504, 2017 | 20 | 2017 |
| The murine transcriptome reveals global aging nodes with organ-specific phase and amplitude N Schaum, B Lehallier, O Hahn, S Hosseinzadeh, SE Lee, R Sit, DP Lee, ... bioRxiv, 662254, 2019 | 19 | 2019 |
| Temporal prediction of retweet count R Pálovics, B Daróczy, AA Benczúr Cognitive Infocommunications (CogInfoCom), 2013 IEEE 4th International …, 2013 | 17 | 2013 |
| Single Cell ADNP Predictive of Human Muscle Disorders: Mouse Knockdown Results in Muscle Wasting O Kapitansky, G Karmon, S Sragovich, A Hadar, M Shahoha, I Jaljuli, ... Cells 9 (10), 2320, 2020 | 14 | 2020 |
| APOE4/4 is linked to damaging lipid droplets in Alzheimer’s microglia MS Haney, R Palovics, CN Munson, C Long, P Johansson, O Yip, ... bioRxiv, 2023 | 13 | 2023 |
| Online ranking prediction in non-stationary environments E Frigó, R Pálovics, D Kelen, L Kocsis, A Benczúr CEUR-WS. org, 2017 | 13 | 2017 |
András BenczúrInstitute for Computer Science and Control確認したメール アドレス: sztaki.hu