AIMC Topic: Tsetse Flies
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Machine Learning Predicts Non-Preferred and Preferred Vertebrate Hosts of Tsetse Flies (Glossina spp.) Based on Skin Volatile Emission Profiles.
Journal of chemical ecology
Mar 7, 2025
Tsetse fly vectors of African trypanosomosis preferentially feed on certain vertebrates largely determined by olfactory cues they emit. Previously, we established that three skin-derived ketones including 6-methyl-5-hepten-2-one, acetophenone and ger...
Deep learning approaches to landmark detection in tsetse wing images.
PLoS computational biology
Jun 26, 2023
Morphometric analysis of wings has been suggested for identifying and controlling isolated populations of tsetse (Glossina spp), vectors of human and animal trypanosomiasis in Africa. Single-wing images were captured from an extensive data set of fie...
Post hoc support vector machine learning for impedimetric biosensors based on weak protein-ligand interactions.
The Analyst
Apr 30, 2018
Impedimetric biosensors for measuring small molecules based on weak/transient interactions between bioreceptors and target analytes are a challenge for detection electronics, particularly in field studies or in the analysis of complex matrices. Prote...
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