Automated Author ProfileGrüning, Björn
Grüning, Björn
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: 3.5 (sum of 5 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The data provided here are part of a Galaxy Training Network tutorial created by Björn Grüning to detect hCNVS in defined WES chromosomal regions.
Authors
- Jumah, Khaled ;
- Grüning, Björn ;
- Poterlowicz, Krzysztof
The data provided here are part of a Galaxy Training Network tutorial created by Björn Grüning to detect hCNVS in defined WES chromosomal regions.
Authors
- Jumah, Khaled ;
- Grüning, Björn ;
- Poterlowicz, Krzysztof
Genome annotation is the process of attaching biological information to sequences. It consists of three main steps:identifying portions of the genome that do not code for proteinsidentifying elements on the genome, a process called gene prediction, andattaching biological information to these elements.
Authors
- Wolff, Joachim ;
- Erxleben, Anika ;
- Grüning, Björn
Genome annotation is the process of attaching biological information to sequences. It consists of three main steps:identifying portions of the genome that do not code for proteinsidentifying elements on the genome, a process called gene prediction, andattaching biological information to these elements.
Authors
- Wolff, Joachim ;
- Erxleben, Anika ;
- Grüning, Björn
The NCBI BLAST suite has become ubiquitous in modern molecular biology and is used for small tasks such as checking capillary sequencing results of single PCR products, genome annotation or even larger scale pan-genome analyses. For early adopters of the Galaxy web-based biomedical data analysis platform, integrating BLAST into Galaxy was a natural step for sequence comparison workflows. Here we provide the command line NCBI BLAST+ tool suite wrapped for use within Galaxy.
The integration of the BLAST+ tool suite into Galaxy has the goal of making common BLAST tasks easy and advanced tasks possible.This project is an informal international collaborative effort, it is deployed and used on Galaxy servers worldwide.
Authors
- Cock, Peter, J.A. ;
- Chilton, John, M. ;
- Grüning, Björn ;
- Johnson, James, E. ;
- Soranzo, Nicola