Automated Author ProfileLiu, Deshuai
Ningxia University
Liu, Deshuai
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: 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
Additional file 2: Table S1. List of primers. Table S2. Mapping features of RNA-seq clean data. Table S3. Differentially expressed genes involved in lipid, carbohydrate and amino acid metabolism pathway. Table S4. The quantity statistics of differentially accumulated metabolites in L. barbarum fruit. Table S5. Model evaluation parameters for metabolomics of L. barbarum fruit samples. Table S6. There are 8 identical differentially accumulated metabolites in the three comparison groups. Table S7. Differential expression results of metabolites and related transcripts. Table S8. Information on key genes and metabolites related to phenylpropane biosynthesis, ascorbic acid, succinate and glutamate metabolism.
Authors
- Liu, Deshuai ;
- Yuan, Miao ;
- Wang, Ye ;
- Zhang, Li ;
- Yao, Wenkong ;
- Feng, Mei
Additional file 2: Table S1. List of primers. Table S2. Mapping features of RNA-seq clean data. Table S3. Differentially expressed genes involved in lipid, carbohydrate and amino acid metabolism pathway. Table S4. The quantity statistics of differentially accumulated metabolites in L. barbarum fruit. Table S5. Model evaluation parameters for metabolomics of L. barbarum fruit samples. Table S6. There are 8 identical differentially accumulated metabolites in the three comparison groups. Table S7. Differential expression results of metabolites and related transcripts. Table S8. Information on key genes and metabolites related to phenylpropane biosynthesis, ascorbic acid, succinate and glutamate metabolism.
Authors
- Liu, Deshuai ;
- Yuan, Miao ;
- Wang, Ye ;
- Zhang, Li ;
- Yao, Wenkong ;
- Feng, Mei