| The GeneCards suite: from gene data mining to disease genome sequence analyses G Stelzer, N Rosen, I Plaschkes, S Zimmerman, M Twik, S Fishilevich, ... Current protocols in bioinformatics 54 (1), 1.30. 1-1.30. 33, 2016 | 3190 | 2016 |
| GeneHancer: genome-wide integration of enhancers and target genes in GeneCards S Fishilevich, R Nudel, N Rappaport, R Hadar, I Plaschkes, T Iny Stein, ... Database 2017, bax028, 2017 | 1055 | 2017 |
| MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search N Rappaport, M Twik, I Plaschkes, R Nudel, T Iny Stein, J Levitt, ... Nucleic acids research 45 (D1), D877-D887, 2017 | 458 | 2017 |
| Gut microbiome pattern reflects healthy ageing and predicts survival in humans T Wilmanski, C Diener, N Rappaport, S Patwardhan, J Wiedrick, ... Nature metabolism 3 (2), 274-286, 2021 | 337 | 2021 |
| MalaCards: an integrated compendium for diseases and their annotation N Rappaport, N Nativ, G Stelzer, M Twik, Y Guan-Golan, T Iny Stein, ... Database 2013, 2013 | 295 | 2013 |
| Blood metabolome predicts gut microbiome α-diversity in humans T Wilmanski, N Rappaport, JC Earls, AT Magis, O Manor, J Lovejoy, ... Nature biotechnology 37 (10), 1217-1228, 2019 | 232 | 2019 |
| GeneAnalytics: an integrative gene set analysis tool for next generation sequencing, RNAseq and microarray data S Ben-Ari Fuchs, I Lieder, G Stelzer, Y Mazor, E Buzhor, S Kaplan, ... Omics: a journal of integrative biology 20 (3), 139-151, 2016 | 217 | 2016 |
| VarElect: the phenotype-based variation prioritizer of the GeneCards Suite G Stelzer, I Plaschkes, D Oz-Levi, A Alkelai, T Olender, S Zimmerman, ... BMC genomics 17, 195-206, 2016 | 198 | 2016 |
| MalaCards: A comprehensive automatically‐mined database of human diseases N Rappaport, M Twik, N Nativ, G Stelzer, I Bahir, TI Stein, M Safran, ... Current Protocols in Bioinformatics 47 (1), 1.24. 1-1.24. 19, 2014 | 95 | 2014 |
| Rational confederation of genes and diseases: NGS interpretation via GeneCards, MalaCards and VarElect N Rappaport, S Fishilevich, R Nudel, M Twik, F Belinky, I Plaschkes, ... Biomedical Engineering Online 16, 1-14, 2017 | 78 | 2017 |
| Multi-omic biological age estimation and its correlation with wellness and disease phenotypes: a longitudinal study of 3,558 individuals JC Earls, N Rappaport, L Heath, T Wilmanski, AT Magis, NJ Schork, ... The Journals of Gerontology: Series A 74 (Supplement_1), S52-S60, 2019 | 59 | 2019 |
| Non-redundant compendium of human ncRNA genes in GeneCards F Belinky, I Bahir, G Stelzer, S Zimmerman, N Rosen, N Nativ, I Dalah, ... Bioinformatics 29 (2), 255-261, 2013 | 55 | 2013 |
| Risk factors for severe COVID-19 differ by age for hospitalized adults S Molani, PV Hernandez, RT Roper, VR Duvvuri, AM Baumgartner, ... Scientific reports 12 (1), 6568, 2022 | 35 | 2022 |
| Genome–microbiome interplay provides insight into the determinants of the human blood metabolome C Diener, CL Dai, T Wilmanski, P Baloni, B Smith, N Rappaport, L Hood, ... Nature metabolism 4 (11), 1560-1572, 2022 | 31 | 2022 |
| Heterogeneity in statin responses explained by variation in the human gut microbiome T Wilmanski, SA Kornilov, C Diener, MP Conomos, JC Lovejoy, ... Med 3 (6), 388-405. e6, 2022 | 28 | 2022 |
| Disentangling signaling gradients generated by equivalent sources N Rappaport, N Barkai Journal of biological physics 38, 267-278, 2012 | 26 | 2012 |
| Multiomic signatures of body mass index identify heterogeneous health phenotypes and responses to a lifestyle intervention K Watanabe, T Wilmanski, C Diener, JC Earls, A Zimmer, B Lincoln, ... Nature medicine 29 (4), 996-1008, 2023 | 25 | 2023 |
| From taxonomy to metabolic output: what factors define gut microbiome health? T Wilmanski, N Rappaport, C Diener, SM Gibbons, ND Price Gut microbes 13 (1), 1907270, 2021 | 23 | 2021 |
| Microglia show differential transcriptomic response to Aβ peptide aggregates ex vivo and in vivo KN McFarland, C Ceballos, A Rosario, T Ladd, B Moore, G Golde, ... Life Science Alliance 4 (7), 2021 | 19 | 2021 |
| Towards early risk biomarkers: serum metabolic signature in childhood predicts cardio-metabolic risk in adulthood X Ojanen, R Cheng, T Törmäkangas, N Rappaport, T Wilmanski, N Wu, ... EBioMedicine 72, 2021 | 18 | 2021 |
