Automated Author ProfileBologna, Paul A. X.
Montclair State University
Bologna, Paul A. X.
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: 0.8 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Next generation sequencing (NGS) methodologies have proven useful in deciphering the food items of generalist predators, but have yet to be applied to gelatinous animal gut and tentacle content. NGS can potentially supplement traditional methods of visual identification. Chrysaora quinquecirrha (Atlantic sea nettle) has progressively become more abundant in Mid-Atlantic United States’ estuaries including Barnegat Bay (New Jersey), potentially having detrimental effects on both marine organisms and human enterprises. Full characterization of this predator's diet is essential for a comprehensive understanding of its impact on the food web and its management. Here we tested the efficacy of NGS for prey item determination in the Atlantic sea nettle. We implemented a NGS “shotgun” approach to randomly sequence DNA fragments isolated from gut lavages and gastric pouch/tentacle picks of 8 and 84 sea nettles, respectively. These results were verified by visual identification and co-occurring plankton tows. Over 550,000 contigs were assembled from ~110 million paired-end reads. Of these, 100 contigs were confidently assigned to 23 different taxa, including soft bodied organisms previously undocumented as prey species, including copepods, fish, ctenophores, anemones, amphipods, barnacles, shrimp, polychaete worms, flukes, flatworms, echinoderms, gastropods, bivalves, and hemichordates. Our results not only indicate that a “shotgun” NGS approach can supplement visual identification methods, but targeted enrichment of a specific amplicon/gene is not a prerequisite for identifying Atlantic sea nettle prey items.
Authors
- Meredith, Robert W. ;
- Gaynor, John J. ;
- Bologna, Paul A.X. ;
- Bologna, Paul A. X.