Automated Author ProfilePapanicolaou, George
Epidemiology Branch, Division of Cardiovascular Sciences, National Heart, Lung and Blood Institute, Bethesda, MD, 20892, USA
Papanicolaou, George
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: 2.1 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This Zenodo file collection contains transcriptome prediction models built for PrediXcan, as well as concatenated raw results from SPrediXcan. Files belong to the scientific research paper: "Multivariate adaptive shrinkage improves cross-population transcriptome prediction for transcriptome-wide association studies in underrepresented populations". Please refer to the README file for a more detailed description.
Authors
- Araujo, Daniel S ;
- Nguyen, Chris ;
- Hu, Xiaowei ;
- Mikhaylova, Anna V ;
- Gignoux, Chris ;
- Ardlie, Kristin ;
- Taylor, Kent D ;
- Durda, Peter ;
- Liu, Yongmei ;
- Papanicolaou, George ;
- Cho, Michael H ;
- Rich, Stephen S ;
- Rotter, Jerome I ;
- NHLBI TOPMed Consortium ;
- Im, Hae Kyung ;
- Manichaikul, Ani ;
- Wheeler, Heather E
This Zenodo file collection contains transcriptome prediction models built for PrediXcan, as well as concatenated raw results from S-PrediXcan. Files belong to the research paper "Multivariate adaptive shrinkage improves cross-population transcriptome prediction and association studies in underrepresented populations" published at HGG Advances (2023, doi: 10.1016/j.xhgg.2023.100216). Please refer to the README file for a more detailed description.
Authors
- Araujo, Daniel S ;
- Nguyen, Chris ;
- Hu, Xiaowei ;
- Mikhaylova, Anna V ;
- Gignoux, Chris ;
- Ardlie, Kristin ;
- Taylor, Kent D ;
- Durda, Peter ;
- Liu, Yongmei ;
- Papanicolaou, George ;
- Cho, Michael H ;
- Rich, Stephen S ;
- Rotter, Jerome I ;
- NHLBI TOPMed Consortium ;
- Im, Hae Kyung ;
- Manichaikul, Ani ;
- Wheeler, Heather E
This Zenodo file collection contains transcriptome prediction models built for PrediXcan, as well as concatenated raw results from S-PrediXcan. Files belong to the research paper "Multivariate adaptive shrinkage improves cross-population transcriptome prediction and association studies in underrepresented populations" published at HGG Advances (2023, doi: 10.1016/j.xhgg.2023.100216). Please refer to the README file for a more detailed description.
Authors
- Araujo, Daniel S ;
- Nguyen, Chris ;
- Hu, Xiaowei ;
- Mikhaylova, Anna V ;
- Gignoux, Chris ;
- Ardlie, Kristin ;
- Taylor, Kent D ;
- Durda, Peter ;
- Liu, Yongmei ;
- Papanicolaou, George ;
- Cho, Michael H ;
- Rich, Stephen S ;
- Rotter, Jerome I ;
- NHLBI TOPMed Consortium ;
- Im, Hae Kyung ;
- Manichaikul, Ani ;
- Wheeler, Heather E