AIMC Topic: DNA Barcoding, Taxonomic

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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...

Review of the genus Shilovia Makarchenko (Diptera: Chironomidae: Diamesinae: Boreoheptagyiini) from the mountains of Central Asia, with morphological description and DNA barcoding of known species.

Zootaxa
Chironomids of the genus Shilovia Makarchenko (Diamesinae, Boreoheptagyiini) from the mountains of Central Asia are revised using both morphological characters and molecular data. Illustrated descriptions of the adult male Shilovia xinhuawangi sp. no...

Scalable classification of organisms into a taxonomy using hierarchical supervised learners.

Journal of bioinformatics and computational biology
Accurately identifying organisms based on their partially available genetic material is an important task to explore the phylogenetic diversity in an environment. Specific fragments in the DNA sequence of a living organism have been defined as DNA ba...