| Electrophilic properties of itaconate and derivatives regulate the IκBζ–ATF3 inflammatory axis M Bambouskova, L Gorvel, V Lampropoulou, A Sergushichev, ... Nature 556 (7702), 501-504, 2018 | 521 | 2018 |
| Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open … J Guinney, T Wang, TD Laajala, KK Winner, JC Bare, EC Neto, SA Khan, ... The Lancet Oncology 18 (1), 132-142, 2017 | 161 | 2017 |
| El-MAVEN: a fast, robust, and user-friendly mass spectrometry data processing engine for metabolomics S Agrawal, S Kumar, R Sehgal, S George, R Gupta, S Poddar, A Jha, ... High-throughput metabolomics: methods and protocols, 301-321, 2019 | 101 | 2019 |
| Multi-tissue acceleration of the mitochondrial phosphoenolpyruvate cycle improves whole-body metabolic health A Abulizi, RL Cardone, R Stark, SL Lewandowski, X Zhao, J Hillion, L Ma, ... Cell metabolism 32 (5), 751-766. e11, 2020 | 51 | 2020 |
| A DREAM challenge to build prediction models for short-term discontinuation of docetaxel in metastatic castration-resistant prostate cancer F Seyednasrollah, DC Koestler, T Wang, SR Piccolo, R Vega, R Greiner, ... JCO clinical cancer informatics 1, 1-15, 2017 | 18 | 2017 |
| Pyruvate kinase M1 suppresses development and progression of prostate adenocarcinoma SM Davidson, DR Schmidt, JE Heyman, JP O'Brien, AC Liu, WJ Israelsen, ... Cancer research 82 (13), 2403-2416, 2022 | 16 | 2022 |
| High-Throughput Metabolomics: Methods and Protocols A D'Alessandro Humana Press, 2019 | 9 | 2019 |
| More than bad luck: Cancer and aging are linked to replication-driven changes to the epigenome CJ Minteer, K Thrush, J Gonzalez, P Niimi, M Rozenblit, J Rozowsky, J Liu, ... Science Advances 9 (29), eadf4163, 2023 | 6 | 2023 |
| in High-Throughput Metabolomics: Methods and Protocols S Agrawal, S Kumar, R Sehgal, S George, R Gupta, S Poddar, A Jha, ... | 6 | 2019 |
| Comprehensive analysis of metabolic isozyme targets in cancer M Marczyk, V Gunasekharan, D Casadevall, T Qing, J Foldi, R Sehgal, ... Cancer research 82 (9), 1698-1711, 2022 | 3 | 2022 |
| Geroscience-Centric Perspective for Geriatric Psychiatry: integrating aging biology with geriatric mental health research BS Diniz, J Seitz-Holland, R Sehgal, J Kasamoto, AT Higgins-Chen, ... The American Journal of Geriatric Psychiatry, 2023 | 2 | 2023 |
| Aging Biomarkers for Clinical Trials and Drug Discovery M Meer, R Sehgal, M Levine Innovation in Aging 5 (Supplement_1), 4-5, 2021 | 2 | 2021 |
| Systems Age: A single blood methylation test to quantify aging heterogeneity across 11 physiological systems R Sehgal, M Meer, AH Shadyab, R Casanova, JAE Manson, P Bhatti, ... bioRxiv, 2023.07. 13.548904, 2023 | 1 | 2023 |
| System specific aging scores: a state of the art aging clock built using aging scores from different bodily functions R Sehgal, A Higgins-Chen, M Meer, M Levine Innovation in Aging 6 (Supplement_1), 20-21, 2022 | 1 | 2022 |
| Abstract P5-17-01: Targeting Acetyl-CoA carboxylase in pre-clinical breast cancer models J Foldi, M Marczyk, V Gunasekharan, T Qing, R Sehgal, NL Shan, ... Cancer Research 82 (4_Supplement), P5-17-01-P5-17-01, 2022 | 1 | 2022 |
| Systems aging clock: A novel epigenetic aging clock modeled from organ & bodily function based mortality indices R Sehgal, M Levine Innovation in Aging 5 (Suppl 1), 1056, 2021 | 1 | 2021 |
| High-throughtput metabolomics A D’alessandro Methods in Molecular Biolog y 1978, 2019 | 1 | 2019 |
| Comprehensive analysis of metabolic isozyme targets in cancerMetabolic isozyme targets in cancer M Marczyk, V Gunasekharan, D Casadevall, T Qing, J Foldi, R Sehgal, ... Cancer Research, 2022 | | 2022 |
| Session 3475 (Symposium) WINHS DURING Innovation in Aging 5 (S1), 2021 | | 2021 |
| Deep Learning Methods Capture Non-Linear Brain Aging Patterns Underlying Alzheimer’s Disease and Resilience K Thrush, A Higgins-Chen, Y Markov, R Sehgal, M Levine Innovation in Aging 5 (Suppl 1), 370, 2021 | | 2021 |
