Automated Author Profiledevit purwoko
devit purwoko
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: 15.4 (sum of 10 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Data for the manuscript " Data on selection of antifungal bacteria for inhibiting the growth of Ganoderma Boninense and their antifungal metabolite compound"
Authors
- devit purwoko
Data for the manuscript " Data on selection of antifungal bacteria for inhibiting the growth of Ganoderma Boninense and their antifungal metabolite compound"
Authors
- devit purwoko
The RNA-seq data was obtained from 3 bulk parts of the rhizome of the temu ireng (C. aeruginosa) representing a complete set of transcriptome data from primary, secondary and tertiary rhizomes produced from 6-month-old plants.
Authors
- devit purwoko
The RNA-seq data was obtained from 3 bulk parts of the rhizome of the temu ireng (C. aeruginosa) representing a complete set of transcriptome data from primary, secondary and tertiary rhizomes produced from 6-month-old plants.
Authors
- devit purwoko
These RNA-seq data were obtained from the selected 3 rice varieties which represent Recalcitrant and Non-recalcitrant complete sets of transcriptome data generated from young tassels when the microspore stage was in the uninucleate stage.
Authors
- devit purwoko
These RNA-seq data were obtained from the selected 3 rice varieties which represent Recalcitrant and Non-recalcitrant complete sets of transcriptome data generated from young tassels when the microspore stage was in the uninucleate stage.
Authors
- devit purwoko
These RNA-seq data were obtained from the selected 3 rice varieties which represent Recalcitrant and Non-recalcitrant complete sets of transcriptome data generated from young tassels when the microspore stage was in the uninucleate stage.
Authors
- devit purwoko
16S Metagenomics OPEFB analysis was conducted in three different old degradations: 6 months, 1 year, and 2 years to understand the microbial community in natural empty fruit bunches degradation.
Authors
- devit purwoko
16S Metagenomics OPEFB analysis was conducted in three different old degradations: 6 months, 1 year, and 2 years to understand the microbial community in natural empty fruit bunches degradation.
Authors
- devit purwoko
16S Metagenomics OPEFB analysis was conducted in three different old degradations: 6 months, 1 year, and 2 years to understand the microbial community in natural empty fruit bunches degradation.
Authors
- devit purwoko