Automated Organization Profile

Grupo de Investigación en Genética Aplicada (GIGA) Instituto de Biología Subtropical (IBS) UNaM-CONICET, Jujuy 1745 N3300NFK Posadas-Misiones ARGENTINA

Current S-Index

4.7

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.6

Average Dataset Index per dataset

Total Datasets

3

Total datasets in this organization

Average FAIR Score

77.6%

Average FAIR Score per dataset

Total Citations

1

Total citations to the organization's datasets

Total Mentions

0

Total mentions of the organization's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Genotypic indexing database (GIDB) for Alouatta caraya

The black and gold howler monkey (Alouatta caraya) is a neotropical primate that faces the highest capture pressure for illegal trade in Argentina. Here, present a Genotypic indexing database (GIDB) this species. Overall, we were able to correctly assign 73% of the individuals in the database to nearest population of origin, and 93.3% to their cluster of origin.

Authors

  • Ines, Luciana
1 Citation0 Mentions79% FAIR1.0 Dataset Index
10.5281/zenodo.33788962019

Genotype reference database (GRDB) for Alouatta caraya

The black and gold howler monkey (Alouatta caraya) is a neotropical primate that faces the highest capture pressure for illegal trade in Argentina. Here, present a Genotype reference database (GRDB) this species. Overall, we were able to correctly assign 73% of the individuals in the database to nearest population of origin, and 93.3% to their cluster of origin.

Authors

  • Oklander, Luciana Ines
0 Citations0 Mentions77% FAIR0.4 Dataset Index
10.5281/zenodo.33788952019

Genotype reference database (GRDB) for Alouatta caraya

The black and gold howler monkey (Alouatta caraya) is a neotropical primate that faces the highest capture pressure for illegal trade in Argentina. Here, present a Genotype reference database (GRDB) this species. Overall, we were able to correctly assign 73% of the individuals in the database to nearest population of origin, and 93.3% to their cluster of origin.

Authors

  • Oklander, Luciana Ines
0 Citations0 Mentions77% FAIR0.4 Dataset Index
10.5281/zenodo.36607232019