dc.contributor.author |
Van Landeghem, Sofie
|
|
dc.contributor.author |
Van Parys, Thomas
|
|
dc.contributor.author |
Dubois, Marieke
|
|
dc.contributor.author |
Inze, Dirk
|
|
dc.contributor.author |
Van de Peer, Yves
|
|
dc.date.accessioned |
2016-05-17T05:49:02Z |
|
dc.date.available |
2016-05-17T05:49:02Z |
|
dc.date.issued |
2016-01-05 |
|
dc.description |
Additional file 1: Overview of the Diffany framework. Overview of the
Diffany framework and its typical usage in a specific experiment involving
the perturbation of an interactome under one or more conditions. (DOCX
183 KB) |
en_ZA |
dc.description |
Additional file 2: List of differentially expressed genes. Dataset of
differentially expressed genes, as originally published by [24]. Here, those
genes are listed that are differentially expressed in at least one of the 4 time
points and in either the more (FDR < 0.05) or less (FDR < 0.1) stringent
dataset. This file also depicts the overlap of genes at the different time
points. (XLSX 514 KB) |
en_ZA |
dc.description |
Additional file 3: Experimental methodology. Methodological details
of the experiments performed on the putative HY5 regulator. (DOCX 22 KB) |
en_ZA |
dc.description |
Additional file 4: Figure showing the experimental validation of the
putative HY5 regulator. Detailed analysis of hy5 mutants and WT lines
when exposed to mannitol-induced stress, comparing both leaf area as
well as expression levels of putative HY5-target genes such as TCH3 and
MYB51. (DOCX 472 KB) |
en_ZA |
dc.description.abstract |
BACKGROUND : Differential networks have recently been introduced as a powerful way to study the dynamic rewiring
capabilities of an interactome in response to changing environmental conditions or stimuli. Currently, such differential
networks are generated and visualised using ad hoc methods, and are often limited to the analysis of only one
condition-specific response or one interaction type at a time.
RESULTS : In this work, we present a generic, ontology-driven framework to infer, visualise and analyse an arbitrary set
of condition-specific responses against one reference network. To this end, we have implemented novel
ontology-based algorithms that can process highly heterogeneous networks, accounting for both physical
interactions and regulatory associations, symmetric and directed edges, edge weights and negation. We propose this
integrative framework as a standardised methodology that allows a unified view on differential networks and
promotes comparability between differential network studies. As an illustrative application, we demonstrate its
usefulness on a plant abiotic stress study and we experimentally confirmed a predicted regulator. |
en_ZA |
dc.description.department |
Genetics |
en_ZA |
dc.description.librarian |
am2016 |
en_ZA |
dc.description.sponsorship |
Ghent University (Multidisciplinary Research
Partnership Bioinformatics: from nucleotides to networks) [to SVL, TVP, YVdP],
the Research Foundation Flanders (FWO) [to SVL], and the Interuniversity
Attraction Poles Program (grant no. P7/29 ‘MARS’) initiated by the Belgian
Science Policy Office, by Ghent University (Bijzonder Onderzoeksfonds
Methusalem project no. BOF08/01M00408, Multidisciplinary Research
Partnership Biotechnology for a Sustainable Economy project no.
01MRB510W) [to MD, DI]. |
en_ZA |
dc.description.uri |
http://www.biomedcentral.com/bmcbioinformatics |
en_ZA |
dc.identifier.citation |
Van Landeghem, S, Van Parys, T, Dubois, M, Inze, D & Van de Peer, Y 2016, 'Diffany : an ontology-driven framework to infer, visualise and analyse differential molecular networks', BMC Bioinformatics, vol. 17, art. 18, pp. 1-12. |
en_ZA |
dc.identifier.issn |
1471-2105 |
|
dc.identifier.other |
10.1186/s12859-015-0863-y |
|
dc.identifier.uri |
http://hdl.handle.net/2263/52641 |
|
dc.language.iso |
en |
en_ZA |
dc.publisher |
BioMed Central |
en_ZA |
dc.rights |
© 2015 Van Landeghem et al. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0
International License. |
en_ZA |
dc.subject |
Differential networks |
en_ZA |
dc.subject |
Osmotic stress response |
en_ZA |
dc.subject |
Systems biology |
en_ZA |
dc.title |
Diffany : an ontology-driven framework to infer, visualise and analyse differential molecular networks |
en_ZA |
dc.type |
Article |
en_ZA |