AIMC Topic: Species Specificity

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Employing fingerprinting of medicinal plants by means of LC-MS and machine learning for species identification task.

Scientific reports
A dataset of liquid chromatography-mass spectrometry measurements of medicinal plant extracts from 74 species was generated and used for training and validating plant species identification algorithms. Various strategies for data handling and feature...

Prediction and functional analysis of prokaryote lysine acetylation site by incorporating six types of features into Chou's general PseAAC.

Journal of theoretical biology
Lysine acetylation is one of the most important types of protein post-translational modifications (PTM) that are widely involved in cellular regulatory processes. To fully understand the regulatory mechanism of acetylation, identification of acetylat...

Large-Scale, High-Resolution Comparison of the Core Visual Object Recognition Behavior of Humans, Monkeys, and State-of-the-Art Deep Artificial Neural Networks.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Primates, including humans, can typically recognize objects in visual images at a glance despite naturally occurring identity-preserving image transformations (e.g., changes in viewpoint). A primary neuroscience goal is to uncover neuron-level mechan...

Enabling Precision Medicine through Integrative Network Models.

Journal of molecular biology
A key challenge in precision medicine lies in understanding molecular-level underpinnings of complex human disease. Biological networks in multicellular organisms can generate hypotheses about disease genes, pathways, and their behavior in disease-re...

Direct Analysis in Real Time-Mass Spectrometry and Kohonen Artificial Neural Networks for Species Identification of Larva, Pupa and Adult Life Stages of Carrion Insects.

Analytical chemistry
Species determination of the various life stages of flies (Order: Diptera) is challenging, particularly for the immature forms, because analogous life stages of different species are difficult to differentiate based on morphological features alone. I...

Semi-supervised machine learning for automated species identification by collagen peptide mass fingerprinting.

BMC bioinformatics
BACKGROUND: Biomolecular methods for species identification are increasingly being utilised in the study of changing environments, both at the microscopic and macroscopic levels. High-throughput peptide mass fingerprinting has been largely applied to...

Supervised machine learning reveals introgressed loci in the genomes of Drosophila simulans and D. sechellia.

PLoS genetics
Hybridization and gene flow between species appears to be common. Even though it is clear that hybridization is widespread across all surveyed taxonomic groups, the magnitude and consequences of introgression are still largely unknown. Thus it is cru...

Disease Ontology: improving and unifying disease annotations across species.

Disease models & mechanisms
Model organisms are vital to uncovering the mechanisms of human disease and developing new therapeutic tools. Researchers collecting and integrating relevant model organism and/or human data often apply disparate terminologies (vocabularies and ontol...

Characterization of Polyphenolic Content in the Aquatic Plants Ruppia cirrhosa and Ruppia maritima -A Source of Nutritional Natural Products.

Molecules (Basel, Switzerland)
Herein, the polyphenolic content in extracts of (Petagna) Grande and L.was fully characterized for the first time. High amounts of the main compound chicoric acid () (≤30.2 ± 4.3 mg/g) were found in both species. In addition, eight flavonoids, nam...