Cross-Species Meta-Analysis of Transcriptomic Data in Combination With Supervised Machine Learning Models Identifies the Common Gene Signature of Lactation Process
- 1Department of Animal Science, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
- 2Department of Biology, University of Qom, Qom, Iran
- 3Adelaide Medical School, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, SA, Australia
- 4Institute of Biotechnology, Shiraz University, Shiraz, Iran
- 5Division of Information Technology, Engineering and the Environment, School of Information Technology & Mathematical Sciences, University of South Australia, Adelaide, SA, Australia
- 6School of Biological Sciences, Faculty of Science and Engineering, Flinders University, Adelaide, SA, Australia
by Farhadian M, Rafat SA, Hasanpur K, Ebrahimi M and Ebrahimie E (2018). Front. Genet. 9:235. doi: 10.3389/fgene.2018.00235
In the original article, we neglected to include the funder “Iran National Science Foundation (INFS), Grant No. 95814261”.
A correction has been made to the Funding statement:
“The authors would like to thank the Iran National Science Foundation (INSF, Grant No. 95814261) for the financial support. We would also like to thank the authorities of Tabriz University.”
The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way.
Keywords: milk production, meta-analysis, microarray, gene ontology, gene network, data mining
Citation: Farhadian M, Rafat SA, Hasanpur K, Ebrahimi M and Ebrahimie E (2019) Corrigendum: Cross-Species Meta-Analysis of Transcriptomic Data in Combination With Supervised Machine Learning Models Identifies the Common Gene Signature of Lactation Process. Front. Genet. 10:1034. doi: 10.3389/fgene.2019.01034
Received: 25 September 2019; Accepted: 26 September 2019;
Published: 16 October 2019.
Approved by: Frontiers Editorial Office, Frontiers Media SA, Switzerland
Copyright © 2019 Farhadian, Rafat, Hasanpur, Ebrahimi and Ebrahimie. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Mohammad Farhadian, mohammad.farhadian@tabrizu.ac.ir; Esmaeil Ebrahimie, esmaeil.ebrahimie@adelaide.edu.au