Automated Author Profile

Malausa, Thibaut

Institut Sophia Agrobiotech

Current S-Index

2.0

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

2.0

Average Dataset Index per dataset

Total Datasets

1

Total datasets for this author

Average FAIR Score

76.9%

Average FAIR Score per dataset

Total Citations

1

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Data from: Statistical analysis of the individual variability of 1D protein profiles as a tool in ecology: an application to parasitoid venom (Version: 1)

Understanding the forces that shape eco-evolutionary patterns often requires linking phenotypes to genotypes, allowing characterization of these patterns at the molecular level. DNA-based markers are less informative in this aim compared to markers associated with gene expression and, more specifically, with protein quantities. The characterization of eco-evolutionary patterns also usually requires the analysis of large sample sizes to accurately estimate interindividual variability. However, the methods used to characterize and compare protein samples are generally expensive and time-consuming, which constrains the size of the produced data sets to few individuals. We present here a method that estimates the interindividual variability of protein quantities based on a global, semi-automatic analysis of 1D electrophoretic profiles, opening the way to rapid analysis and comparison of hundreds of individuals. The main original features of the method are the in silico normalization of sample protein quantities using pictures of electrophoresis gels at different staining levels, as well as a new method of analysis of electrophoretic profiles based on a median profile. We demonstrate that this method can accurately discriminate between species and between geographically distant or close populations, based on interindividual variation in venom protein profiles from three endoparasitoid wasps of two different genera (Psyttalia concolor, Psyttalia lounsburyi and Leptopilina boulardi). Finally, we discuss the experimental designs that would benefit from the use of this method.

Authors

  • Mathé-Hubert, Hugo ;
  • Gatti, Jean-Luc ;
  • Colinet, Dominique ;
  • Poirié, Marylène ;
  • Malausa, Thibaut
1 Citation0 Mentions77% FAIR2.0 Dataset Index
10.5061/dryad.d1d1mFebruary 2015