ArticleJournal of forensic sciences2018
Bioinformatics Approach to Assess the Biogeographical Patterns of Soil Communities: The Utility for Soil Provenance.
Article in Journal of forensic sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Spatiotemporal dynamics of soil bacterial and fungal communities at a small scale.Frontiers in microbiology · 2026Article
- Salinity Impacts the FunctionalMicroorganisms · 2023Article
- Environmental DNA as an innovative technique to identify the origins of falsified antimalarial tablets-a pilot study of the pharmabiome.Scientific reports · 2022Article
- Rare genera differentiate urban green space soil bacterial communities in three cities across the world.Access microbiology · 2022Article
- On the Identification of Body Fluids and Tissues: A Crucial Link in the Investigation and Solution of Crime.Genes · 2021Review
- Geographic source estimation using airborne plant environmental DNA in dust.Scientific reports · 2021Article
- Microbiomes in forensic botany: a review.Forensic science, medicine, and pathology · 2021Review
- The Future of Environmental DNA in Forensic Science.Applied and environmental microbiology · 2020Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Soil DNA profiling has potential as a forensic tool to establish a link between soil collected at a crime scene and soil recovered from a suspect. However, a quantitative measure is needed to investigate the spatial/temporal variability across multiple scales prior to their application in forensic science. In this study, soil DNA profiles across Miami-Dade, FL, were generated using length heterogeneity PCR to target four taxa. The objectives of this study were to (i) assess the biogeographical patterns of soils to determine whether soil biota is spatially correlated with geographic location and (ii) evaluate five machine learning algorithms for their predictive ability to recognize biotic patterns which could accurately classify soils at different spatial scales regardless of seasonal collection. Results demonstrate that soil communities have unique patterns and are spatially autocorrelated. Bioinformatic algorithms could accurately classify soils across all scales with Random Forest significantly outperforming all other algorithms regardless of spatial level.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.