Automated Author ProfileShao, Lin
Burning Rock Biotech (China)
Shao, Lin
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: 7.4 (sum of 8 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Additional file 6. Table S3: List of 72 transcription factor genes the field cancerization-specific differentially methylated regions spanned and significantly enriched GO terms.
Authors
- Wang, Qiushi ;
- Wu, Libo ;
- Yu, Jiaxing ;
- Li, Guanghua ;
- Zhang, Pengfei ;
- Wang, Haozhe ;
- Shao, Lin ;
- Liu, Jinying ;
- Shen, Weixi
Additional file 5. Table S2: Results of GSEA analysis using different MsigDB gene sets. Analysis 1 used “KEGG gene sets as NCBI (Entrez) Gene IDs” (c2.cp.kegg.v7.4.entrez.gmt), and the corresponding significantly enriched KEG pathways are shown in Figures 3A and 3B. Analysis 2 used ll canonical pathways as NCBI (Entrez) Gene IDs (c2.cp.v7.4.entrez.gmt), and the corresponding significantly enriched KEGG pathways aer shown in Figure S1).
Authors
- Wang, Qiushi ;
- Wu, Libo ;
- Yu, Jiaxing ;
- Li, Guanghua ;
- Zhang, Pengfei ;
- Wang, Haozhe ;
- Shao, Lin ;
- Liu, Jinying ;
- Shen, Weixi
Additional file 6. Table S3: List of 72 transcription factor genes the field cancerization-specific differentially methylated regions spanned and significantly enriched GO terms.
Authors
- Wang, Qiushi ;
- Wu, Libo ;
- Yu, Jiaxing ;
- Li, Guanghua ;
- Zhang, Pengfei ;
- Wang, Haozhe ;
- Shao, Lin ;
- Liu, Jinying ;
- Shen, Weixi
Additional file 4. Table S1: Details of tumor-specific differentially methylated regions.
Authors
- Wang, Qiushi ;
- Wu, Libo ;
- Yu, Jiaxing ;
- Li, Guanghua ;
- Zhang, Pengfei ;
- Wang, Haozhe ;
- Shao, Lin ;
- Liu, Jinying ;
- Shen, Weixi
Additional file 4. Table S1: Details of tumor-specific differentially methylated regions.
Authors
- Wang, Qiushi ;
- Wu, Libo ;
- Yu, Jiaxing ;
- Li, Guanghua ;
- Zhang, Pengfei ;
- Wang, Haozhe ;
- Shao, Lin ;
- Liu, Jinying ;
- Shen, Weixi
Additional file 5. Table S2: Results of GSEA analysis using different MsigDB gene sets. Analysis 1 used “KEGG gene sets as NCBI (Entrez) Gene IDs” (c2.cp.kegg.v7.4.entrez.gmt), and the corresponding significantly enriched KEG pathways are shown in Figures 3A and 3B. Analysis 2 used ll canonical pathways as NCBI (Entrez) Gene IDs (c2.cp.v7.4.entrez.gmt), and the corresponding significantly enriched KEGG pathways aer shown in Figure S1).
Authors
- Wang, Qiushi ;
- Wu, Libo ;
- Yu, Jiaxing ;
- Li, Guanghua ;
- Zhang, Pengfei ;
- Wang, Haozhe ;
- Shao, Lin ;
- Liu, Jinying ;
- Shen, Weixi
Additional file 1. List of the 520 genes in the OncoScreen panel.
Authors
- Liu, Changjiang ;
- Liu, Chengang ;
- Zou, Xiao ;
- Shao, Lin ;
- Sun, Ying ;
- Guo, Yang
Additional file 1. List of the 520 genes in the OncoScreen panel.
Authors
- Liu, Changjiang ;
- Liu, Chengang ;
- Zou, Xiao ;
- Shao, Lin ;
- Sun, Ying ;
- Guo, Yang