Automated Author ProfileHuanqing Xu
Huanqing Xu
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author'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: 0.6 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Additional file 2: Table S1. Trait variation and heritability in the parental lines and three RIL mapping populations. Table S2. Pearson’s correlation coefficients (r) between all investigated traits of RILs across years and three mapping populations. Table S3. Principal component analysis (PCA) on the three RIL mapping populations. Table S4. Summary of detected QTL for all investigated traits in the three RIL populations acoss years. Table S5. Epistasis QTL for the investigated traits in the three RIL populations acoss years. Table S6. Predicted candidate genes associated with leaf related traits and chlorophyll content in six major QTL regions. Table S7. Gene Ontology (GO) enrichment analysis of six major QTLregoins associated with leaf related traits and chlorophyll content.
Authors
- Kaiye Yu ;
- Jinshe Wang ;
- Chongyuan Sun ;
- Xiaoqian Liu ;
- Huanqing Xu ;
- Yuming Yang ;
- Lidong Dong ;
- Zhang, Dan
Additional file 2: Table S1. Trait variation and heritability in the parental lines and three RIL mapping populations. Table S2. Pearson’s correlation coefficients (r) between all investigated traits of RILs across years and three mapping populations. Table S3. Principal component analysis (PCA) on the three RIL mapping populations. Table S4. Summary of detected QTL for all investigated traits in the three RIL populations acoss years. Table S5. Epistasis QTL for the investigated traits in the three RIL populations acoss years. Table S6. Predicted candidate genes associated with leaf related traits and chlorophyll content in six major QTL regions. Table S7. Gene Ontology (GO) enrichment analysis of six major QTLregoins associated with leaf related traits and chlorophyll content.
Authors
- Kaiye Yu ;
- Jinshe Wang ;
- Chongyuan Sun ;
- Xiaoqian Liu ;
- Huanqing Xu ;
- Yuming Yang ;
- Lidong Dong ;
- Zhang, Dan