Automated Organization ProfileAndré Márcio Amorim, & Instituto de Biologia, Universidade Federal da Bahia (UFBA), Rua Barão de Jeremoabo, Ondina, 40170 - 115, Salvador, Bahia, Brazil
André Márcio Amorim, & Instituto de Biologia, Universidade Federal da Bahia (UFBA), Rua Barão de Jeremoabo, Ondina, 40170 - 115, Salvador, Bahia, Brazil
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets in this organization
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the organization's datasets
Total Mentions
Total mentions of the organization's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.0 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Table 1. Assembly and target enrichment statistics per sample of Ochnaceae and its major clades.Clade (number of individuals) aCleaned readsOn-target readsOn-target reads (sample-specific)Enrichment efficiency (%) bEnrichment efficiency, sample-specific (%)Loci recovered (sample specific)Loci recovered (consensus alignment)Mean read depth, FAM data (×) cMean read depth, LEO data (×) cOchnaceae (all) (n = 264)1,857, 078 (77,784 – 7,025,814)508,699 (839– 3,357,298)351,455 (1,495– 1,829,919)26. 3 (0.1– 78.2)19.7 (0.4 –46.3)226 (34– 273)188 (2 – 257)408 (23 – 2403)223 (7 – 1484)Ochneae (n = 199)1,901, 558 (136,360 – 7,025,814)668,893 (24,573 – 3,357,298)415,907 (1,495 – 1,829,919)34. 3 (3.1 – 78.2)22. 4 (0.4 –46.3)227 (34 – 273)225 (70 – 257)467 (26 – 2403)224 (7 – 1484)Sauvagesieae (n = 47)1,941, 757 (77,784 – 5,692,105)23,410 (839– 133,181)151,388 (5,177– 431,763)2. 0 (0.1– 20.6)9. 6 (0.5 –32.2)222 (53– 266)79 (2 – 165)223 (23 – 619)naLuxemburgieae & Testulea (n = 14)1,096, 178 (551,202 – 1,776,229)27,126 (11,899 – 53,015)190,333 (61,089 –569,881)2.7 (0.9 – 5.3)18.7 (4.2 –35.3)227 (110 – 268)85 (51 – 109)246 (108 – 580)naQuiinoideae & Medusagyne (n = 4)1,254, 609 (316,141 – 2,304,830)13,556 (4,640 –18,289)113,871 (56,531 – 169,167)1. 3 (0.8 – 1.6)11. 1 (7.3 – 17.9)204 (163 – 246)35 (17 – 57)186 (80 – 284)na
Authors
- Schneider, Julio V. ;
- Jungcurt, Tanja ;
- Cardoso, Domingos ;
- Amorim, André Márcio ;
- Töpel, Mats ;
- Andermann, Tobias ;
- Poncy, Odile ;
- Berberich, Thomas ;
- Zizka, Georg
Table 1. Assembly and target enrichment statistics per sample of Ochnaceae and its major clades.Clade (number of individuals) aCleaned readsOn-target readsOn-target reads (sample-specific)Enrichment efficiency (%) bEnrichment efficiency, sample-specific (%)Loci recovered (sample specific)Loci recovered (consensus alignment)Mean read depth, FAM data (×) cMean read depth, LEO data (×) cOchnaceae (all) (n = 264)1,857, 078 (77,784 – 7,025,814)508,699 (839– 3,357,298)351,455 (1,495– 1,829,919)26. 3 (0.1– 78.2)19.7 (0.4 –46.3)226 (34– 273)188 (2 – 257)408 (23 – 2403)223 (7 – 1484)Ochneae (n = 199)1,901, 558 (136,360 – 7,025,814)668,893 (24,573 – 3,357,298)415,907 (1,495 – 1,829,919)34. 3 (3.1 – 78.2)22. 4 (0.4 –46.3)227 (34 – 273)225 (70 – 257)467 (26 – 2403)224 (7 – 1484)Sauvagesieae (n = 47)1,941, 757 (77,784 – 5,692,105)23,410 (839– 133,181)151,388 (5,177– 431,763)2. 0 (0.1– 20.6)9. 6 (0.5 –32.2)222 (53– 266)79 (2 – 165)223 (23 – 619)naLuxemburgieae & Testulea (n = 14)1,096, 178 (551,202 – 1,776,229)27,126 (11,899 – 53,015)190,333 (61,089 –569,881)2.7 (0.9 – 5.3)18.7 (4.2 –35.3)227 (110 – 268)85 (51 – 109)246 (108 – 580)naQuiinoideae & Medusagyne (n = 4)1,254, 609 (316,141 – 2,304,830)13,556 (4,640 –18,289)113,871 (56,531 – 169,167)1. 3 (0.8 – 1.6)11. 1 (7.3 – 17.9)204 (163 – 246)35 (17 – 57)186 (80 – 284)na
Authors
- Schneider, Julio V. ;
- Jungcurt, Tanja ;
- Cardoso, Domingos ;
- Amorim, André Márcio ;
- Töpel, Mats ;
- Andermann, Tobias ;
- Poncy, Odile ;
- Berberich, Thomas ;
- Zizka, Georg