Artificial Intelligence and Classical Methods in Animal Genetics and Breeding

— Basic methods of population genetics and animal breeding and mathematical methods of machine learning used in animal breeding are analyzed. CatBoost library models were trained on the example of two domesticated species—horse ( Equus caballus ) and reindeer ( Rangifer tarandus ). Data from microsa...

Full description

Saved in:
Bibliographic Details
Published inRussian journal of genetics Vol. 60; no. 7; pp. 843 - 856
Main Authors Soloshenkov, A. D., Soloshenkova, E. A., Semina, M. T., Spasskaya, N. N., Voronkova, V. N., Stolpovsky, Y. A.
Format Journal Article
LanguageEnglish
Published Moscow Pleiades Publishing 01.07.2024
Subjects
Animal Genetics and Genomics
Biomedical and Life Sciences
Biomedicine
Human Genetics
Microbial Genetics and Genomics
Reviews and Theoretical Articles
horse
animal husbandry
genetic diversity
reindeer
neural networks
microsatellite analysis
machine learning
Online AccessGet full text

Cover

More Information
Summary:— Basic methods of population genetics and animal breeding and mathematical methods of machine learning used in animal breeding are analyzed. CatBoost library models were trained on the example of two domesticated species—horse ( Equus caballus ) and reindeer ( Rangifer tarandus ). Data from microsatellite panels of loci 16 and 17, respectively, were used to train the model using data on domesticated and wild reindeer, European and Russian horse breeds. The standard indicators (Accuracy, Precision, Recall, and F1 ) were calculated, and confusion matrices were constructed to assess the success of the model. New possibilities for identifying animal breed affiliation are shown.
ISSN:1022-7954
1608-3369
DOI:10.1134/S1022795424700297