Automated Author ProfileSamrat Chatterjee
Samrat Chatterjee
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: 4.9 (sum of 6 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Text S1. Mathematical representation of traversing a directed network. Validation of ranked lists from other temporal datasets. (ZIP 302 kb)
Authors
- Rajat Anand ;
- Dipanka Sarmah ;
- Samrat Chatterjee
Text S1. Mathematical representation of traversing a directed network. Validation of ranked lists from other temporal datasets. (ZIP 302 kb)
Authors
- Rajat Anand ;
- Dipanka Sarmah ;
- Samrat Chatterjee
Ranking of proteins using algorithm made in the paper and collective influence algorithm and results from controllability algorithm. (XLSX 140 kb)
Authors
- Rajat Anand ;
- Dipanka Sarmah ;
- Samrat Chatterjee
Ranking of proteins using algorithm made in the paper and collective influence algorithm and results from controllability algorithm. (XLSX 140 kb)
Authors
- Rajat Anand ;
- Dipanka Sarmah ;
- Samrat Chatterjee
The matlab code of the algorithm made in the study. Contains the input example small dataset and the output resultant biclusters obtained by application of algorithm on the given small dataset. (XLSX 197 kb)
Authors
- Rajat Anand ;
- Srikanth Ravichandran ;
- Samrat Chatterjee
The matlab code of the algorithm made in the study. Contains the input example small dataset and the output resultant biclusters obtained by application of algorithm on the given small dataset. (XLSX 197 kb)
Authors
- Rajat Anand ;
- Srikanth Ravichandran ;
- Samrat Chatterjee