Automated Author ProfileGath, Emily
Gath, Emily
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: 0.9 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
See "Data files-README.md" for description of each data archive (TAR/GZIP). The processed strain inhibition data is located in sGR_reference_set_gsk_brd4310_archive.tar.gz. TB PROSPECT standardized Growth Rate (sGR) scores of 333 hypomorphs and 7 WT H37Rv control strains against each compound-concentration (condition) from a 437 compound reference set with existing, published MOA screened in dose-response, 173 GSK compounds from a publicly released antitubercular collection that were screened blinded and in dose-response, and BRD4310 pre-selected from an unbiased chemical library and screened in dose-response. As described in "Data files-README.md", the other archived data files are inputs or results from the application of our reference-based MOA prediction method, PCL analysis, based on comparing chemical-genetic interaction profiles of test compounds to those of the reference set compounds with annotated MOA. GCTx format is a binary file used to store the scores in matrix format with annotated row and column metadata in a compressed, memory-efficient manner. Code libraries in Matlab (cmapM), Python (cmapPy), and R (cmapR) are publicly available on Github to work with it. The GCT format can be visualized, sorted, and filtered on Morpheus, https://software.broadinstitute.org/morpheus.
Authors
- Bond, Austin ;
- Orzechowski, Marek ;
- Zhang, Shuting ;
- Ben-Zion, Ishay ;
- Lemmer, Allison ;
- Garry, Nathaniel ;
- Lee, Katie ;
- Chen, Michael ;
- Delano, Kayla ;
- Gath, Emily ;
- Lorelei Golas, A. ;
- Nietupski, Raymond ;
- Fitzgerald, Michael ;
- Ehrt, Sabine ;
- Rubin, Eric J. ;
- Sassetti, Christopher M ;
- Schnappinger, Dirk ;
- Shoresh, Noam ;
- Hunt, Diana ;
- Gomez, James E. ;
- Hung, Deborah T.