@article{HansenMeyerFerrarietal.2017,
  author    = {Hansen, Bjoern Oest and Meyer, Etienne H. and Ferrari, Camilla and Vaid, Neha and Movahedi, Sara and Vandepoele, Klaas and Nikoloski, Zoran and Mutwil, Marek},
  title     = {Ensemble gene function prediction database reveals genes important for complex I formation in Arabidopsis thaliana},
  series = {New phytologist : international journal of plant science},
  volume    = {217},
  journal   = {New phytologist : international journal of plant science},
  number    = {4},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {0028-646X},
  doi       = {10.1111/nph.14921},
  pages     = {1521 -- 1534},
  year      = {2017},
  abstract  = {Recent advances in gene function prediction rely on ensemble approaches that integrate results from multiple inference methods to produce superior predictions. Yet, these developments remain largely unexplored in plants. We have explored and compared two methods to integrate 10 gene co-function networks for Arabidopsis thaliana and demonstrate how the integration of these networks produces more accurate gene function predictions for a larger fraction of genes with unknown function. These predictions were used to identify genes involved in mitochondrial complex I formation, and for five of them, we confirmed the predictions experimentally. The ensemble predictions are provided as a user-friendly online database, EnsembleNet. The methods presented here demonstrate that ensemble gene function prediction is a powerful method to boost prediction performance, whereas the EnsembleNet database provides a cutting-edge community tool to guide experimentalists.},
  language  = {en}
}
@article{AnnunziataApeltCarilloetal.2017,
  author    = {Annunziata, Maria Grazia and Apelt, Federico and Carillo, Petronia and Krause, Ursula and Feil, Regina and Mengin, Virginie and Lauxmann, Martin A. and Koehl, Karin and Nikoloski, Zoran and Stitt, Mark and Lunn, John Edward},
  title     = {Getting back to nature: a reality check for experiments in controlled environments},
  series = {Journal of experimental botany},
  volume    = {68},
  journal   = {Journal of experimental botany},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  issn      = {0022-0957},
  doi       = {10.1093/jxb/erx220},
  pages     = {4463 -- 4477},
  year      = {2017},
  abstract  = {Irradiance from sunlight changes in a sinusoidal manner during the day, with irregular fluctuations due to clouds, and light-dark shifts at dawn and dusk are gradual. Experiments in controlled environments typically expose plants to constant irradiance during the day and abrupt light-dark transitions. To compare the effects on metabolism of sunlight versus artificial light regimes, Arabidopsis thaliana plants were grown in a naturally illuminated greenhouse around the vernal equinox, and in controlled environment chambers with a 12-h photoperiod and either constant or sinusoidal light profiles, using either white fluorescent tubes or light-emitting diodes (LEDs) tuned to a sunlight-like spectrum as the light source. Rosettes were sampled throughout a 24-h diurnal cycle for metabolite analysis. The diurnal metabolite profiles revealed that carbon and nitrogen metabolism differed significantly between sunlight and artificial light conditions. The variability of sunlight within and between days could be a factor underlying these differences. Pairwise comparisons of the artificial light sources (fluorescent versus LED) or the light profiles (constant versus sinusoidal) showed much smaller differences. The data indicate that energy-efficient LED lighting is an acceptable alternative to fluorescent lights, but results obtained from plants grown with either type of artificial lighting might not be representative of natural conditions.},
  language  = {en}
}