The genome-scale metabolic model for the purple non-sulfur bacterium Rhodopseudomonas palustris Bis A53 accurately predicts phenotypes under chemoheterotrophic, chemoautotrophic, photoheterotrophic, and photoautotrophic growth conditions

Diego Tec-Campos, Camila Posadas, Juan D. Tibocha-Bonilla, Deepan Thiruppathy, Nathan Glonek, Cristal Zuñiga, Alejandro Zepeda, Karsten Zengler. The genome-scale metabolic model for the purple non-sulfur bacterium Rhodopseudomonas palustris Bis A53 accurately predicts phenotypes under chemoheterotrophic, chemoautotrophic, photoheterotrophic, and photoautotrophic growth conditions. PLoS Computational Biology, 19(8), 2023. [doi]

@article{Tec-CamposPTTGZ23,
  title = {The genome-scale metabolic model for the purple non-sulfur bacterium Rhodopseudomonas palustris Bis A53 accurately predicts phenotypes under chemoheterotrophic, chemoautotrophic, photoheterotrophic, and photoautotrophic growth conditions},
  author = {Diego Tec-Campos and Camila Posadas and Juan D. Tibocha-Bonilla and Deepan Thiruppathy and Nathan Glonek and Cristal Zuñiga and Alejandro Zepeda and Karsten Zengler},
  year = {2023},
  doi = {10.1371/journal.pcbi.1011371},
  url = {https://doi.org/10.1371/journal.pcbi.1011371},
  researchr = {https://researchr.org/publication/Tec-CamposPTTGZ23},
  cites = {0},
  citedby = {0},
  journal = {PLoS Computational Biology},
  volume = {19},
  number = {8},
}