| An Arabidopsis gene regulatory network for secondary cell wall synthesis M Taylor-Teeples, L Lin, M De Lucas, G Turco, TW Toal, A Gaudinier, ... Nature 517 (7536), 571-575, 2015 | 651 | 2015 |
| Predictive behavior within microbial genetic networks I Tagkopoulos, YC Liu, S Tavazoie science 320 (5881), 1313-1317, 2008 | 481 | 2008 |
| Benzalkonium chlorides: uses, regulatory status, and microbial resistance B Merchel Piovesan Pereira, I Tagkopoulos Applied and environmental microbiology 85 (13), e00377-19, 2019 | 296 | 2019 |
| From vital signs to clinical outcomes for patients with sepsis: a machine learning basis for a clinical decision support system E Gultepe, JP Green, H Nguyen, J Adams, T Albertson, I Tagkopoulos Journal of the American Medical Informatics Association 21 (2), 315-325, 2014 | 215 | 2014 |
| Evolutionary potential, cross‐stress behavior and the genetic basis of acquired stress resistance in Escherichia coli M Dragosits, V Mozhayskiy, S Quinones‐Soto, J Park, I Tagkopoulos Molecular systems biology 9 (1), 643, 2013 | 178 | 2013 |
| Multi-omics integration accurately predicts cellular state in unexplored conditions for Escherichia coli M Kim, N Rai, V Zorraquino, I Tagkopoulos Nature communications 7 (1), 13090, 2016 | 155 | 2016 |
| Transcriptional network analysis identifies BACH1 as a master regulator of breast cancer bone metastasis Y Liang, H Wu, R Lei, RA Chong, Y Wei, X Lu, I Tagkopoulos, SY Kung, ... Journal of Biological Chemistry 287 (40), 33533-33544, 2012 | 139 | 2012 |
| From data to optimal decision making: a data-driven, probabilistic machine learning approach to decision support for patients with sepsis A Tsoukalas, T Albertson, I Tagkopoulos JMIR medical informatics 3 (1), e3445, 2015 | 108 | 2015 |
| An integrative, multi‐scale, genome‐wide model reveals the phenotypic landscape of Escherichia coli J Carrera, R Estrela, J Luo, N Rai, A Tsoukalas, I Tagkopoulos Molecular systems biology 10 (7), 735, 2014 | 100 | 2014 |
| Data integration and predictive modeling methods for multi-omics datasets M Kim, I Tagkopoulos Molecular omics 14 (1), 8-25, 2018 | 94 | 2018 |
| Application of machine learning in rheumatic disease research KJ Kim, I Tagkopoulos The Korean journal of internal medicine 34 (4), 708, 2019 | 83 | 2019 |
| A synthetic biology approach to self-regulatory recombinant protein production in Escherichia coli M Dragosits, D Nicklas, I Tagkopoulos Journal of biological engineering 6, 1-10, 2012 | 60 | 2012 |
| Biocide-induced emergence of antibiotic resistance in Escherichia coli B Merchel Piovesan Pereira, X Wang, I Tagkopoulos Frontiers in Microbiology 12, 640923, 2021 | 53 | 2021 |
| SBROME: a scalable optimization and module matching framework for automated biosystems design L Huynh, A Tsoukalas, M Köppe, I Tagkopoulos ACS synthetic biology 2 (5), 263-273, 2013 | 53 | 2013 |
| Kinetic characterization of 100 glycoside hydrolase mutants enables the discovery of structural features correlated with kinetic constants DA Carlin, RW Caster, X Wang, SA Betzenderfer, CX Chen, VM Duong, ... PLoS One 11 (1), e0147596, 2016 | 52 | 2016 |
| Predicting early risk of chronic kidney disease in cats using routine clinical laboratory tests and machine learning R Bradley, I Tagkopoulos, M Kim, Y Kokkinos, T Panagiotakos, J Kennedy, ... Journal of veterinary internal medicine 33 (6), 2644-2656, 2019 | 50 | 2019 |
| The Genetic and Transcriptional Basis of Short and Long Term Adaptation across Multiple Stresses in Escherichia coli V Zorraquino, M Kim, N Rai, I Tagkopoulos Molecular Biology and Evolution 34 (3), 707-717, 2017 | 50 | 2017 |
| Compendium of skin molecular signatures identifies key pathological features associated with fibrosis in systemic sclerosis SJ Moon, JM Bae, KS Park, I Tagkopoulos, KJ Kim Annals of the Rheumatic Diseases 78 (6), 817-825, 2019 | 36 | 2019 |
| The computational diet: a review of computational methods across diet, microbiome, and health A Eetemadi, N Rai, BMP Pereira, M Kim, H Schmitz, I Tagkopoulos Frontiers in Microbiology 11, 393, 2020 | 35 | 2020 |
| Predicting the evolution of Escherichia coli by a data-driven approach X Wang, V Zorraquino, M Kim, A Tsoukalas, I Tagkopoulos Nature communications 9 (1), 3562, 2018 | 35 | 2018 |
Minseung KimUniversity of California, DavisBestätigte E-Mail-Adresse bei vidio.ai
