Ghent University Academic Bibliography

Advanced

Ensemble gene function prediction database reveals genes important for complex I formation in Arabidopsis thaliana

Bjoern Oest Hansen, Etienne H Meyer, Camilla Ferrari, Neha Vaid, Sara Movahedi, Klaas Vandepoele UGent, Zoran Nikoloski and Marek Mutwil (2018) NEW PHYTOLOGIST. 217(4). p.1521-1534
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.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
PROTEIN FUNCTION PREDICTION, COEXPRESSION NETWORKS, SUBUNIT NDUFV3, MODULES, PLANTS, IDENTIFICATION, INTEGRATION, EUKARYOTES, RESOURCE, ISOFORMS, Arabidopsis thaliana, co-function network, complex I, ensemble, prediction, gene function prediction
journal title
NEW PHYTOLOGIST
New Phytol.
volume
217
issue
4
pages
1521 - 1534
Web of Science type
Article
Web of Science id
000424284400015
ISSN
0028-646X
1469-8137
DOI
10.1111/nph.14921
project
Bioinformatics: from nucleotids to networks (N2N)
language
English
UGent publication?
yes
classification
A1
additional info
the first two authors contributed equally to this work
copyright statement
I have transferred the copyright for this publication to the publisher
id
8558094
handle
http://hdl.handle.net/1854/LU-8558094
date created
2018-04-03 11:26:53
date last changed
2018-04-11 12:32:18
@article{8558094,
  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.},
  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},
  issn         = {0028-646X},
  journal      = {NEW PHYTOLOGIST},
  keyword      = {PROTEIN FUNCTION PREDICTION,COEXPRESSION NETWORKS,SUBUNIT NDUFV3,MODULES,PLANTS,IDENTIFICATION,INTEGRATION,EUKARYOTES,RESOURCE,ISOFORMS,Arabidopsis thaliana,co-function network,complex I,ensemble,prediction,gene function prediction},
  language     = {eng},
  number       = {4},
  pages        = {1521--1534},
  title        = {Ensemble gene function prediction database reveals genes important for complex I formation in Arabidopsis thaliana},
  url          = {http://dx.doi.org/10.1111/nph.14921},
  volume       = {217},
  year         = {2018},
}

Chicago
Hansen, Bjoern Oest, Etienne H Meyer, Camilla Ferrari, Neha Vaid, Sara Movahedi, Klaas Vandepoele, Zoran Nikoloski, and Marek Mutwil. 2018. “Ensemble Gene Function Prediction Database Reveals Genes Important for Complex I Formation in Arabidopsis Thaliana.” New Phytologist 217 (4): 1521–1534.
APA
Hansen, B. O., Meyer, E. H., Ferrari, C., Vaid, N., Movahedi, S., Vandepoele, K., Nikoloski, Z., et al. (2018). Ensemble gene function prediction database reveals genes important for complex I formation in Arabidopsis thaliana. NEW PHYTOLOGIST, 217(4), 1521–1534.
Vancouver
1.
Hansen BO, Meyer EH, Ferrari C, Vaid N, Movahedi S, Vandepoele K, et al. Ensemble gene function prediction database reveals genes important for complex I formation in Arabidopsis thaliana. NEW PHYTOLOGIST. 2018;217(4):1521–34.
MLA
Hansen, Bjoern Oest, Etienne H Meyer, Camilla Ferrari, et al. “Ensemble Gene Function Prediction Database Reveals Genes Important for Complex I Formation in Arabidopsis Thaliana.” NEW PHYTOLOGIST 217.4 (2018): 1521–1534. Print.