@article{PandeyYuOmranianetal.2019, author = {Pandey, Prashant K. and Yu, Jing and Omranian, Nooshin and Alseekh, Saleh and Vaid, Neha and Fernie, Alisdair R. and Nikoloski, Zoran and Laitinen, Roosa A. E.}, title = {Plasticity in metabolism underpins local responses to nitrogen in Arabidopsis thaliana populations}, series = {Plant Direct}, volume = {3}, journal = {Plant Direct}, number = {11}, publisher = {John Wiley \& sonst LTD}, address = {Chichester}, issn = {2475-4455}, doi = {10.1002/pld3.186}, pages = {6}, year = {2019}, abstract = {Nitrogen (N) is central for plant growth, and metabolic plasticity can provide a strategy to respond to changing N availability. We showed that two local A. thaliana populations exhibited differential plasticity in the compounds of photorespiratory and starch degradation pathways in response to three N conditions. Association of metabolite levels with growth-related and fitness traits indicated that controlled plasticity in these pathways could contribute to local adaptation and play a role in plant evolution.}, language = {en} } @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} }