Search: onr:"swepub:oai:DiVA.org:su-106341" >
Functional associat...
Functional association networks as priors for gene regulatory network inference
-
- Studham, Matthew E. (author)
- Stockholms universitet,Institutionen för biokemi och biofysik,Science for Life Laboratory (SciLifeLab)
-
- Tjärnberg, Andreas (author)
- Stockholms universitet,Institutionen för biokemi och biofysik,Science for Life Laboratory (SciLifeLab)
-
- Nordling, Torbjörn (author)
- Uppsala universitet,Cancer och vaskulärbiologi
-
show more...
-
- Nelander, Sven (author)
- Uppsala universitet,Cancer och vaskulärbiologi
-
- Sonnhammer, Erik L. L. (author)
- Stockholms universitet,Institutionen för biokemi och biofysik,Science for Life Laboratory (SciLifeLab),Swedish e-Science Research Center, Sweden
-
show less...
-
(creator_code:org_t)
- 2014-06-11
- 2014
- English.
-
In: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 30:12, s. 130-138
- Related links:
-
https://doi.org/10.1...
-
show more...
-
https://academic.oup...
-
https://uu.diva-port... (primary) (Raw object)
-
https://urn.kb.se/re...
-
https://doi.org/10.1...
-
https://urn.kb.se/re...
-
show less...
Abstract
Subject headings
Close
- Motivation: Gene regulatory network (GRN) inference reveals the influences genes have on one another in cellular regulatory systems. If the experimental data are inadequate for reliable inference of the network, informative priors have been shown to improve the accuracy of inferences. Results: This study explores the potential of undirected, confidence-weighted networks, such as those in functional association databases, as a prior source for GRN inference. Such networks often erroneously indicate symmetric interaction between genes and may contain mostly correlation-based interaction information. Despite these drawbacks, our testing on synthetic datasets indicates that even noisy priors reflect some causal information that can improve GRN inference accuracy. Our analysis on yeast data indicates that using the functional association databases FunCoup and STRING as priors can give a small improvement in GRN inference accuracy with biological data.
Subject headings
- NATURVETENSKAP -- Biologi -- Biokemi och molekylärbiologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences -- Biochemistry and Molecular Biology (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Bioinformatics (hsv//eng)
- NATURVETENSKAP -- Biologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences (hsv//eng)
Keyword
- Biochemistry towards Bioinformatics
- biokemi med inriktning mot bioinformatik
Publication and Content Type
- ref (subject category)
- art (subject category)
Find in a library
To the university's database