AIMC Topic: Animals

Clear Filters Showing 6031 to 6040 of 8866 articles

Combined use of two supervised learning algorithms to model sea turtle behaviours from tri-axial acceleration data.

The Journal of experimental biology
Accelerometers are becoming ever more important sensors in animal-attached technology, providing data that allow determination of body posture and movement and thereby helping to elucidate behaviour in animals that are difficult to observe. We sought...

Multiclassification Prediction of Enzymatic Reactions for Oxidoreductases and Hydrolases Using Reaction Fingerprints and Machine Learning Methods.

Journal of chemical information and modeling
Drug metabolism is a complex procedure in the human body, including a series of enzymatically catalyzed reactions. However, it is costly and time consuming to investigate drug metabolism experimentally; computational methods are hence developed to pr...

High vacuum and aspiration on phacoemulsification efficiency and chatter for Centurion.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
OBJECTIVE: To compare relative efficiency and chatter of high aspiration and vacuum settings.

Mapping Cellular Polarity Networks Using Mass Spectrometry-based Strategies.

Journal of molecular biology
Cell polarity is a vital biological process involved in the building, maintenance and normal functioning of tissues in invertebrates and vertebrates. Unsurprisingly, molecular defects affecting polarity organization and functions have a strong impact...

Consistent prediction of GO protein localization.

Scientific reports
The GO-Cellular Component (GO-CC) ontology provides a controlled vocabulary for the consistent description of the subcellular compartments or macromolecular complexes where proteins may act. Current machine learning-based methods used for the automat...

Modeling Dengue vector population using remotely sensed data and machine learning.

Acta tropica
Mosquitoes are vectors of many human diseases. In particular, Aedes ægypti (Linnaeus) is the main vector for Chikungunya, Dengue, and Zika viruses in Latin America and it represents a global threat. Public health policies that aim at combating this v...

Effluent composition prediction of a two-stage anaerobic digestion process: machine learning and stoichiometry techniques.

Environmental science and pollution research international
Computational self-adapting methods (Support Vector Machines, SVM) are compared with an analytical method in effluent composition prediction of a two-stage anaerobic digestion (AD) process. Experimental data for the AD of poultry manure were used. Th...

Cell dynamic morphology classification using deep convolutional neural networks.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Cell morphology is often used as a proxy measurement of cell status to understand cell physiology. Hence, interpretation of cell dynamic morphology is a meaningful task in biomedical research. Inspired by the recent success of deep learning, we here ...

Predicting lysine-malonylation sites of proteins using sequence and predicted structural features.

Journal of computational chemistry
Malonylation is a recently discovered post-translational modification (PTM) in which a malonyl group attaches to a lysine (K) amino acid residue of a protein. In this work, a novel machine learning model, SPRINT-Mal, is developed to predict malonylat...

Harnessing the evolutionary information on oxygen binding proteins through Support Vector Machines based modules.

BMC research notes
OBJECTIVES: The arrival of free oxygen on the globe, aerobic life is becoming possible. However, it has become very clear that the oxygen binding proteins are widespread in the biosphere and are found in all groups of organisms, including prokaryotes...