AIMC Topic: DNA Barcoding, Taxonomic

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The apportionment of dietary diversity in wildlife.

Proceedings of the National Academy of Sciences of the United States of America
Evaluating species' roles in food webs is critical for advancing ecological theories on competition, coexistence, and biodiversity but is complicated by pronounced dietary variability within species and overlap across species. We combined dietary DNA...

Machine learning-based mapping of Acidobacteriota and Planctomycetota using 16 S rRNA gene metabarcoding data across soils in Russia.

Scientific reports
The soil microbiome plays a crucial role in maintaining healthy ecosystems and supporting sustainable agriculture. Studying its biogeographical structure and distribution is essential for understanding the rates and mechanisms of microbially mediated...

Illuminating Entomological Dark Matter with DNA Barcodes in an Era of Insect Decline, Deep Learning, and Genomics.

Annual review of entomology
Most insects encountered in the field are initially entomological dark matter in that they cannot be identified to species while alive. This explains the enduring quest for efficient ways to identify collected specimens. Morphological tools came firs...

Integrating external stressors in supervised machine learning algorithm achieves high accuracy to predict multi-species biological integrity index of aquaculture wastewater.

Journal of hazardous materials
Monitoring and predicting the environmental impact of wastewater is essential for sustainable aquaculture. The environmental DNA metabarcoding-integrated supervised machine learning (SML) algorithm is an alternative method for ecological quality asse...

Development of a two-layer machine learning model for the forensic application of legal and illegal poppy classification based on sequence data.

Forensic science international. Genetics
Poppies are beneficial plants with a variety of applications, including medicinal, edible, ornamental, and industrial purposes. Some Papaver species are forensically significant plants because they contain opium, a narcotic substance. Internationally...

New deep learning-based methods for visualizing ecosystem properties using environmental DNA metabarcoding data.

Molecular ecology resources
Environmental DNA (eDNA) metabarcoding provides an efficient approach for documenting biodiversity patterns in marine and terrestrial ecosystems. The complexity of these data prevents current methods from extracting and analyzing all the relevant eco...

Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks.

Proceedings of the National Academy of Sciences of the United States of America
Taxonomic classification, that is, the assignment to biological clades with shared ancestry, is a common task in genetics, mainly based on a genome similarity search of large genome databases. The classification quality depends heavily on the databas...

DeepBarcoding: Deep Learning for Species Classification Using DNA Barcoding.

IEEE/ACM transactions on computational biology and bioinformatics
DNA barcodes with short sequence fragments are used for species identification. Because of advances in sequencing technologies, DNA barcodes have gradually been emphasized. DNA sequences from different organisms are easily and rapidly acquired. There...

DiversityScanner: Robotic handling of small invertebrates with machine learning methods.

Molecular ecology resources
Invertebrate biodiversity remains poorly understood although it comprises much of the terrestrial animal biomass, most species and supplies many ecosystem services. The main obstacle is specimen-rich samples obtained with quantitative sampling techni...