Automated Author ProfilePerri, Ami
Perri, Ami
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: 11.1 (sum of 22 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Missense Variants Identified In 6 Patients Or More (XLSX 11Â kb)
Authors
- Eliseos Mucaki ;
- Caminsky, Natasha ;
- Perri, Ami ;
- Ruipeng Lu ;
- Laederach, Alain ;
- Halvorsen, Matthew ;
- Knoll, Joan ;
- Rogan, Peter
Variants identified within natural donor or acceptor splice sites (XLSX 14Â kb)
Authors
- Eliseos Mucaki ;
- Caminsky, Natasha ;
- Perri, Ami ;
- Ruipeng Lu ;
- Laederach, Alain ;
- Halvorsen, Matthew ;
- Knoll, Joan ;
- Rogan, Peter
Variants Predicted by IT to Affect SRFBSs (XLSX 30Â kb)
Authors
- Eliseos Mucaki ;
- Caminsky, Natasha ;
- Perri, Ami ;
- Ruipeng Lu ;
- Laederach, Alain ;
- Halvorsen, Matthew ;
- Knoll, Joan ;
- Rogan, Peter
TFs For Which Information Weight Matrices Were Built And Factorâ s Role in Transcription (XLSX 17Â kb)
Authors
- Eliseos Mucaki ;
- Caminsky, Natasha ;
- Perri, Ami ;
- Ruipeng Lu ;
- Laederach, Alain ;
- Halvorsen, Matthew ;
- Knoll, Joan ;
- Rogan, Peter
All Flagged and Prioritized Variants by Patient (XLSX 26Â kb)
Authors
- Eliseos Mucaki ;
- Caminsky, Natasha ;
- Perri, Ami ;
- Ruipeng Lu ;
- Laederach, Alain ;
- Halvorsen, Matthew ;
- Knoll, Joan ;
- Rogan, Peter
Top Changes in RBBSs Predicted by IT for Variants Predicted to Significantly Alter RNA Structure (XLSX 10Â kb)
Authors
- Eliseos Mucaki ;
- Caminsky, Natasha ;
- Perri, Ami ;
- Ruipeng Lu ;
- Laederach, Alain ;
- Halvorsen, Matthew ;
- Knoll, Joan ;
- Rogan, Peter
Missense Variants and Their Classification (XLSX 27Â kb)
Authors
- Eliseos Mucaki ;
- Caminsky, Natasha ;
- Perri, Ami ;
- Ruipeng Lu ;
- Laederach, Alain ;
- Halvorsen, Matthew ;
- Knoll, Joan ;
- Rogan, Peter
Primer Sequences for Sanger Sequencing of Likely Pathogenic Variants (XLSX 10Â kb)
Authors
- Eliseos Mucaki ;
- Caminsky, Natasha ;
- Perri, Ami ;
- Ruipeng Lu ;
- Laederach, Alain ;
- Halvorsen, Matthew ;
- Knoll, Joan ;
- Rogan, Peter
UTR Sequences Used for SHAPE Analysis on SNPfold-flagged Variants (XLSX 9Â kb)
Authors
- Eliseos Mucaki ;
- Caminsky, Natasha ;
- Perri, Ami ;
- Ruipeng Lu ;
- Laederach, Alain ;
- Halvorsen, Matthew ;
- Knoll, Joan ;
- Rogan, Peter
Variants Predicted by IT to Affect TFBSs (XLSX 14Â kb)
Authors
- Eliseos Mucaki ;
- Caminsky, Natasha ;
- Perri, Ami ;
- Ruipeng Lu ;
- Laederach, Alain ;
- Halvorsen, Matthew ;
- Knoll, Joan ;
- Rogan, Peter