Please use this identifier to cite or link to this item:
Title: Ensemble gene function prediction database reveals genes important for complex I formation in Arabidopsis thaliana
Authors: Hansen, Bjoern Oest
Meyer, Etienne H.
Ferrari, Camilla
Vaid, Neha
Movahedi, Sara
Vandepoele, Klaas
Nikoloski, Zoran
Mutwil, Marek
Keywords: Gene Function Prediction
DRNTU::Science::Biological sciences
Ensemble Prediction
Issue Date: 2018
Source: Hansen, B. O., Meyer, E. H., Ferrari, C., Vaid, N., Movahedi, S., Vandepoele, K., . . . Mutwil, M. (2018). Ensemble gene function prediction database reveals genes important for complex I formation in Arabidopsis thaliana. New Phytologist, 217(4), 1521-1534. doi:10.1111/nph.14921
Series/Report no.: New Phytologist
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.
ISSN: 0028-646X
DOI: 10.1111/nph.14921
Rights: © 2017 New Phytologist Trust. All rights reserved. This paper was published by Wiley in New Phytologist and is made available with permission of New Phytologist Trust. The definitive version is available at via
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SBS Journal Articles

Citations 20

Updated on Sep 5, 2020

Citations 50

Updated on Nov 26, 2020

Page view(s)

Updated on Nov 30, 2020

Download(s) 50

Updated on Nov 30, 2020

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.