Automated Author ProfileMeiklejohn, Kelly A
Meiklejohn, Kelly A
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: 15.0 (sum of 26 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
In this National Institute of Justice funded grant, two types of surface soils representing scenarios that would potentially benefit the most from new quantitative methods were collected from across the state of North Carolina (USA) in April 2022: a) similar inorganic content but with distinct land use (category type = mineral rich), and b) those with limited inorganic content but recognizable organic fractions (category type = organic rich). At each location (n, 30), samples were collected from paired sites <500 meters apart (A and B). At each paired site, three sub-site samples were collected 1 meter apart to assess method reproducibility, accuracy and small-scale variation that might be realistically observed in questioned-to-known (Q-to-K) comparisons (total n, ~180). Each sample was subjected to examination using methods currently used in practice (e.g., manual color determination, polarized light microscopy, x-ray diffraction), along with three new quantitative methods: 1) instrumental colorimetry, 2) automated scanning electron microscopy energy dispersive X-ray spectroscopy of soil minerals, and 3) DNA metabarcoding of plant, bacteria, arthropods and fungi.
Authors
- Meiklejohn, Kelly A
Files associated with the publication "Evaluating Non-Destructive Sampling Methods of Parchment for Genomic Sequencing" by Diaz et al. 2025.FASTA file (Authenticated mt genome sequences.fa) - Consensus mitochondrial genome (mtGenome) sequences of authenticated samples. Only samples with consensus sequences with >10 X coverage are included.EXCEL file (Sample Metadata.xlsx) - metadata on the sample ID, parchment ID, non-destructive sampling method along with whether it is included in the FASTA file.
Authors
- Diaz, Lindsey ;
- Scheible, Melissa KR ;
- Stinson, Timothy L. ;
- Livingston, Isabella ;
- Breen, Matthew ;
- Meiklejohn, Kelly A
Files associated with the publication "Evaluating Non-Destructive Sampling Methods of Parchment for Genomic Sequencing" by Diaz et al. 2025.FASTA file (Authenticated mt genome sequences.fa) - Consensus mitochondrial genome (mtGenome) sequences of authenticated samples. Only samples with consensus sequences with >10 X coverage are included.EXCEL file (Sample Metadata.xlsx) - metadata on the sample ID, parchment ID, non-destructive sampling method along with whether it is included in the FASTA file.
Authors
- Diaz, Lindsey ;
- Scheible, Melissa KR ;
- Stinson, Timothy L. ;
- Livingston, Isabella ;
- Breen, Matthew ;
- Meiklejohn, Kelly A
In this National Institute of Justice funded grant, two types of surface soils representing scenarios that would potentially benefit the most from new quantitative methods were collected from across the state of North Carolina (USA) in April 2022: a) similar inorganic content but with distinct land use (category type = mineral rich), and b) those with limited inorganic content but recognizable organic fractions (category type = organic rich). At each location (n, 30), samples were collected from paired sites <500 meters apart (A and B). At each paired site, three sub-site samples were collected 1 meter apart to assess method reproducibility, accuracy and small-scale variation that might be realistically observed in questioned-to-known (Q-to-K) comparisons (total n, ~180). Each sample was subjected to examination using methods currently used in practice (e.g., manual color determination, polarized light microscopy, x-ray diffraction), along with three new quantitative methods: 1) instrumental colorimetry, 2) automated scanning electron microscopy energy dispersive X-ray spectroscopy of soil minerals, and 3) DNA metabarcoding of plant, bacteria, arthropods and fungi.
Authors
- Meiklejohn, Kelly A
Table providing a list of the ITS2 amplicon sequence variants (ASVs) included in final dataset (n, 1574) and the number of reads recovered for each in each sample. Sample name abbreviations are as follows: PA, Pennsylvannia; CO, Colorado; NC, North Carolina; PS, PowerSoil Kit; PSP, PowerSoil Pro Kit; 65, 65oC incubation; 90, 90oC incubation; US, unspiked; NS, normal spiked; PNS, partial spiked; RB, reagent blank.
Authors
- Moore, Madison A ;
- Scheible, Melissa KR ;
- Robertson, James B ;
- Meiklejohn, Kelly A
Table providing a list of the ITS2 amplicon sequence variants (ASVs) included in final dataset (n, 1574) and the number of reads recovered for each in each sample. Sample name abbreviations are as follows: PA, Pennsylvannia; CO, Colorado; NC, North Carolina; PS, PowerSoil Kit; PSP, PowerSoil Pro Kit; 65, 65oC incubation; 90, 90oC incubation; US, unspiked; NS, normal spiked; PNS, partial spiked; RB, reagent blank.
The publication associated with this data is: Moore MA, Scheible MKR, Robertson JB and Meiklejohn KA (2022). Assessing the lysis of diverse pollen from bulk environmental samples for DNA metabarcoding. Metabarcoding and Metagenomics.
Authors
- Moore, Madison A ;
- Scheible, Melissa KR ;
- Robertson, James B ;
- Meiklejohn, Kelly A
Specimen information and barcode results for plant sequences when searched against GenBank and BOLD.
Authors
- Meiklejohn, Kelly A ;
- Damaso, Natalie ;
- Robertson, James M
Specimen information and barcode results for macro-fungi ITS sequences when searched against GenBank and BOLD.
Authors
- Meiklejohn, Kelly A ;
- Damaso, Natalie
Specimen information and barcode results for insect COI sequences when searched against GenBank and BOLD.
Authors
- Meiklejohn, Kelly A ;
- Damaso, Natalie ;
- Robertson, James M
Primers and thermal cycling conditions used to amplify each barcoding region for insects, macro-fungi, and plants.
Authors
- Meiklejohn, Kelly A ;
- Damaso, Natalie ;
- Robertson, James M