ArticleJournal of neuroscience methods2011
Profiling a Caenorhabditis elegans behavioral parametric dataset with a supervised K-means clustering algorithm identifies genetic networks regulating locomotion.
Article in Journal of neuroscience methods, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed, 16 citations in OpenAlex.
- Inherent instability of the retinitis pigmentosa P23H mutant opsin.The Journal of biological chemistry · 2014Article
- A dictionary of behavioral motifs reveals clusters of genes affecting Caenorhabditis elegans locomotion.Proceedings of the National Academy of Sciences of the United States of America · 2013Article
- Expression of mammalian G protein-coupled receptors in Caenorhabditis elegans.Methods in enzymology · 2013Article
- Tackling thermosensation with multidimensional phenotyping.BMC biology · 2012Article
- Calcium imaging of multiple neurons in freely behaving C. elegans.Journal of neuroscience methods · 2012Article
- Heterologous expression of functional G-protein-coupled receptors in Caenorhabditis elegans.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2012Article
- Light-sensitive coupling of rhodopsin and melanopsin to G(i/o) and G(q) signal transduction in Caenorhabditis elegans.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2012Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
Defining genetic networks underlying animal behavior in a high throughput manner is an important but challenging task that has not yet been achieved for any organism. Using Caenorhabditis elegans, we collected quantitative parametric data related to various aspects of locomotion from wild type and 31 mutant worm strains with single mutations in genes functioning in sensory reception, neurotransmission, G-protein signaling, neuromuscular control or other facets of motor regulation. We applied unsupervised and constrained K-means clustering algorithms to the data and found that the genes that clustered together due to the behavioral similarity of their mutants encoded proteins in the same signaling networks. This approach provides a framework to identify genes and genetic networks underlying worm neuromotor function in a high-throughput manner. A publicly accessible database harboring the visual and quantitative behavioral data collected in this study adds valuable information to the rapidly growing C. elegans databanks that can be employed in a similar context.
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Registered trials
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