Automated Author Profile
Yang, Youlong
Xidian University

Current S-Index

5.2

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.5

Average Dataset Index per dataset

Total Datasets

10

Total datasets for this author

Average FAIR Score

84.6%

Average FAIR Score per dataset

Total Citations

0

Total citations to the author's datasets

Total Mentions

0

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: 5.2 (sum of 10 datasets Dataset Index scores)

More information here.

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Additional file 2 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data

Additional file 2.

Authors

Zhu, Jiadi ;
Yang, Youlong

0 Citations0 Mentions85% FAIR0.5 Dataset Index

10.6084/m9.figshare.265917592024

Additional file 2 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data

Additional file 2.

Authors

Zhu, Jiadi ;
Yang, Youlong

0 Citations0 Mentions85% FAIR0.5 Dataset Index

10.6084/m9.figshare.26591759.v12024

Additional file 3 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data

Additional file 3.

Authors

Zhu, Jiadi ;
Yang, Youlong

0 Citations0 Mentions85% FAIR0.5 Dataset Index

10.6084/m9.figshare.265917622024

Additional file 3 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data

Additional file 3.

Authors

Zhu, Jiadi ;
Yang, Youlong

0 Citations0 Mentions85% FAIR0.5 Dataset Index

10.6084/m9.figshare.26591762.v12024

Additional file 4 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data

Additional file 4.

Authors

Zhu, Jiadi ;
Yang, Youlong

0 Citations0 Mentions85% FAIR0.5 Dataset Index

10.6084/m9.figshare.265917652024

Additional file 4 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data

Additional file 4.

Authors

Zhu, Jiadi ;
Yang, Youlong

0 Citations0 Mentions85% FAIR0.5 Dataset Index

10.6084/m9.figshare.26591765.v12024

Additional file 5 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data

Additional file 5.

Authors

Zhu, Jiadi ;
Yang, Youlong

0 Citations0 Mentions85% FAIR0.5 Dataset Index

10.6084/m9.figshare.265917682024

Additional file 5 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data

Additional file 5.

Authors

Zhu, Jiadi ;
Yang, Youlong

0 Citations0 Mentions85% FAIR0.5 Dataset Index

10.6084/m9.figshare.26591768.v12024

Additional file 6 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data

Additional file 6.

Authors

Zhu, Jiadi ;
Yang, Youlong

0 Citations0 Mentions85% FAIR0.5 Dataset Index

10.6084/m9.figshare.265917712024

Additional file 6 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data

Additional file 6.

Authors

Zhu, Jiadi ;
Yang, Youlong

0 Citations0 Mentions85% FAIR0.5 Dataset Index

10.6084/m9.figshare.26591771.v12024