| Leveraging knowledge engineering and machine learning for microbial bio-manufacturing T Oyetunde, FS Bao, JW Chen, HG Martin, YJ Tang Biotechnology advances 36 (4), 1308-1315, 2018 | 83 | 2018 |
| Rapid prediction of bacterial heterotrophic fluxomics using machine learning and constraint programming SG Wu, Y Wang, W Jiang, T Oyetunde, R Yao, X Zhang, K Shimizu, ... PLoS computational biology 12 (4), e1004838, 2016 | 83 | 2016 |
| Decoupling resource-coupled gene expression in living cells T Shopera, L He, T Oyetunde, YJ Tang, TS Moon ACS synthetic biology 6 (8), 1596-1604, 2017 | 82 | 2017 |
| Machine learning framework for assessment of microbial factory performance T Oyetunde, D Liu, HG Martin, YJ Tang PloS one 14 (1), e0210558, 2019 | 68 | 2019 |
| BoostGAPFILL: improving the fidelity of metabolic network reconstructions through integrated constraint and pattern-based methods T Oyetunde, M Zhang, Y Chen, Y Tang, C Lo Bioinformatics 33 (4), 608-611, 2017 | 60 | 2017 |
| Integrated knowledge mining, genome-scale modeling, and machine learning for predicting Yarrowia lipolytica bioproduction JJ Czajka, T Oyetunde, YJ Tang Metabolic Engineering 67, 227-236, 2021 | 46 | 2021 |
| Recovering metabolic networks using a novel hyperlink prediction method M Zhang, Z Cui, T Oyetunde, Y Tang, Y Chen arXiv preprint arXiv:1610.06941, 2016 | 25 | 2016 |
| Exploring eukaryotic formate metabolisms to enhance microbial growth and lipid accumulation Z Liu, T Oyetunde, WD Hollinshead, A Hermanns, YJ Tang, W Liao, Y Liu Biotechnology for Biofuels 10, 1-9, 2017 | 20 | 2017 |
| Extracting particle size distribution from laser speckle with a physics-enhanced autocorrelation-based estimator (PEACE) Q Zhang, JC Gamekkanda, A Pandit, W Tang, C Papageorgiou, C Mitchell, ... Nature communications 14 (1), 1159, 2023 | 18 | 2023 |
| Thermal imaging-based state estimation of a Stefan problem with application to cell thawing P Srisuma, A Pandit, Q Zhang, MS Hong, J Gamekkanda, F Fachin, ... Computers & Chemical Engineering 173, 108179, 2023 | 6 | 2023 |
| A multiple reaction modelling framework for microbial electrochemical technologies T Oyetunde, PM Sarma, F Ahmad, J Rodríguez International Journal of Molecular Sciences 18 (1), 86, 2017 | 5 | 2017 |
| Linear, funnel, and multiple funnel schemes for stacking chromosomes that carry targeted recombinations in plants T Oyetunde, R Bernardo Theoretical and Applied Genetics 133, 3177-3186, 2020 | 4 | 2020 |
| Modeling Bioelectrochemical Systems for Waste Water Treatment and Bioenergy Recovery with COMSOL Multiphysics® T Oyetunde, D Ofiteru, J Rodriguez Proceedings of the 2013 COMSOL conference in Boston, 2013 | 2 | 2013 |
| Biofuels from coastal deserts: The sustainability case for a Salicornia bigelovii-based biorefinery A Alassali, T Oyetunde, K Rashid, J Rodríguez, J Schmidt, MH Thomsen | 2 | 2013 |
| From Laser Speckle to Particle Size Distribution in drying powders: A Physics-Enhanced AutoCorrelation-based Estimator (PEACE) Q Zhang, J Gamekkanda, W Tang, C Papageorgiou, C Mitchell, Y Yang, ... | 1 | 2022 |
| Metabolite patterns reveal regulatory responses to genetic perturbations T Oyetunde, J Czajka, G Wu, C Lo, Y Tang arXiv preprint arXiv:1701.01744, 2017 | 1 | 2017 |
| Laser Speckle Probe for Monitoring Pharmaceutical Drying A Pandit, Q Zhang, MS Hong, W Tang, CD Papageorgiou, N Nazemifard, ... 2023 AIChE Annual Meeting, 2023 | | 2023 |
| Quantitative Speckle Analysis to Estimate Surface Particle Size Distribution Q Zhang, JC Gamekkanda, A Pandit, W Tang, C Papageorgiou, ... Computational Optical Sensing and Imaging, CW5B. 4, 2023 | | 2023 |
| Decoding Complexity in Metabolic Networks using Integrated Mechanistic and Machine Learning Approaches T Oyetunde Washington University in St. Louis, 2018 | | 2018 |
| A Deep Learning Framework Decodes Coordination of Microbial Metabolism Under Genetic and Environmental Perturbations T Oyetunde, J Czajka, Y Tang 2017 AIChE Annual Meeting, 2017 | | 2017 |
Muhan ZhangPeking UniversityZweryfikowany adres z pku.edu.cn