AIMC Topic: Species Specificity

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A k-mer-based barcode DNA classification methodology based on spectral representation and a neural gas network.

Artificial intelligence in medicine
OBJECTIVES: In this paper, an alignment-free method for DNA barcode classification that is based on both a spectral representation and a neural gas network for unsupervised clustering is proposed.

Fish locomotion: recent advances and new directions.

Annual review of marine science
Research on fish locomotion has expanded greatly in recent years as new approaches have been brought to bear on a classical field of study. Detailed analyses of patterns of body and fin motion and the effects of these movements on water flow patterns...

Inter-species pathway perturbation prediction via data-driven detection of functional homology.

Bioinformatics (Oxford, England)
MOTIVATION: Experiments in animal models are often conducted to infer how humans will respond to stimuli by assuming that the same biological pathways will be affected in both organisms. The limitations of this assumption were tested in the IMPROVER ...

Towards the automatized identification of moss species from their spore morphology.

Annals of botany
BACKGROUND AND AIMS: Automatized species identification tools have massively facilitated plant identification. In mosses, spore ultrastructure appears to be a promising taxonomic character, but has been largely under-exploited. Here, we test artifici...

Sequence-driven species identification of ZooMS collagen peptide mass fingerprints.

Journal of proteomics
Developments in biomolecular species identification of animal tissues have been ongoing for decades, with collagen peptide mass fingerprinting becoming increasingly used in recent years. However, establishing confidence in the species biomarkers with...

Interspecies predictions of growth traits from quantitative transcriptome data acquired during fruit development.

Journal of experimental botany
Linking genotype and phenotype is a fundamental challenge in biology. In this respect, machine learning is playing a pivotal role in systems biology. As central phenotypic traits, fruit development and relative growth rate (RGR) result from interacti...

A classification-occupancy model based on automatically identified species data.

Ecology
Occupancy models estimate a species' occupancy probability while accounting for imperfect detection, but often overlook the issue of false-positive detections. This problem of false positives has gained attention recently with the rapid advancement o...

Reported liver toxicity of food chemicals in rats extrapolated to humans using virtual human-to-rat hepatic concentration ratios generated by pharmacokinetic modeling with machine learning-derived parameters.

The Journal of toxicological sciences
Pharmacokinetic data are not generally available for evaluating the toxicological potential of food chemicals. A simplified physiologically based pharmacokinetic (PBPK) model has been established to evaluate internal exposures to chemicals in rats or...

Sequence-Based Machine Learning Reveals 3D Genome Differences between Bonobos and Chimpanzees.

Genome biology and evolution
The 3D structure of the genome is an important mediator of gene expression. As phenotypic divergence is largely driven by gene regulatory variation, comparing genome 3D contacts across species can further understanding of the molecular basis of speci...

INTREPPPID-an orthologue-informed quintuplet network for cross-species prediction of protein-protein interaction.

Briefings in bioinformatics
An overwhelming majority of protein-protein interaction (PPI) studies are conducted in a select few model organisms largely due to constraints in time and cost of the associated 'wet lab' experiments. In silico PPI inference methods are ideal tools t...