Automated Author ProfileDhakan, Darshan
Dhakan, Darshan
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: 10.9 (sum of 18 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Table S4. Abundance of KEGG Pathways in the Yamuna. Table S5. Abundance of KEGG Orthologs in the Yamuna. Table S6. The antibiotic resistant genes identified in the Yamuna samples a) In YJ b) In YN. Table S7. Category wise Abundance of Antibiotic Resistant Genes. Table S8. List of metal resistance/tolerant genes identified in Yamuna and its count. Table S9. Abundance of KEGG Pathways in the five datasets. (XLSX 780 kb)
Authors
- Mittal, Parul ;
- Vishnu Prasoodanan PK ;
- Dhakan, Darshan ;
- Kumar, Sanjiv ;
- Sharma, Vineet
Table S4. Abundance of KEGG Pathways in the Yamuna. Table S5. Abundance of KEGG Orthologs in the Yamuna. Table S6. The antibiotic resistant genes identified in the Yamuna samples a) In YJ b) In YN. Table S7. Category wise Abundance of Antibiotic Resistant Genes. Table S8. List of metal resistance/tolerant genes identified in Yamuna and its count. Table S9. Abundance of KEGG Pathways in the five datasets. (XLSX 780 kb)
Authors
- Mittal, Parul ;
- Vishnu Prasoodanan PK ;
- Dhakan, Darshan ;
- Kumar, Sanjiv ;
- Sharma, Vineet
Categorization of peptidoglycan hydrolases into four different classes on the basis of their site of action and composition of Negative Dataset as the fifth class. (XLSX 8Â kb)
Authors
- Sharma, Ashok ;
- Kumar, Sanjiv ;
- Harish, K. ;
- Dhakan, Darshan ;
- Sharma, Vineet
Metagenomic datasets used for evaluation of performance. (XLSX 9Â kb)
Authors
- Sharma, Ashok ;
- Kumar, Sanjiv ;
- Harish, K. ;
- Dhakan, Darshan ;
- Sharma, Vineet
Instructions for running the stand-alone version of HyPe on the Linux PC. (TXT 845 bytes)
Authors
- Sharma, Ashok ;
- Kumar, Sanjiv ;
- Harish, K. ;
- Dhakan, Darshan ;
- Sharma, Vineet
Performance of HyPe on independent genomic dataset. (XLSX 9Â kb)
Authors
- Sharma, Ashok ;
- Kumar, Sanjiv ;
- Harish, K. ;
- Dhakan, Darshan ;
- Sharma, Vineet
Comparison of performance of all the three approaches on a Metagenomic dataset. (XLSX 8Â kb)
Authors
- Sharma, Ashok ;
- Kumar, Sanjiv ;
- Harish, K. ;
- Dhakan, Darshan ;
- Sharma, Vineet
Performance of HyPe on independent metagenomic dataset. (XLSX 9Â kb)
Authors
- Sharma, Ashok ;
- Kumar, Sanjiv ;
- Harish, K. ;
- Dhakan, Darshan ;
- Sharma, Vineet
Performance of HyPe on independent metagenomic dataset. (XLSX 9Â kb)
Authors
- Sharma, Ashok ;
- Kumar, Sanjiv ;
- Harish, K. ;
- Dhakan, Darshan ;
- Sharma, Vineet
Comparison of performance of the three approaches using known 250 peptidoglycan hydrolases. (XLSX 8Â kb)
Authors
- Sharma, Ashok ;
- Kumar, Sanjiv ;
- Harish, K. ;
- Dhakan, Darshan ;
- Sharma, Vineet