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Network Biology, 2021, 11(1): 29-43
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Article

Validation of forward-in-time method using artificial neural network: the application in a biological system

Abdurahim Kalajdzic1, Samim Konjicija2, Belma Kalamujic Stroil1, Naris Pojskic1
1Institute for Genetic Engineering and Biotechnology, University of Sarajevo, Zmaja od Bosne 8 (Kampus), Sarajevo 71000, Bosnia and Herzegovina
2Faculty of Electrical Engineering, University of Sarajevo, Zmaja od Bosne bb (Kampus), Sarajevo 71000, Bosnia and Herzegovina

Received 23 October 2020;Accepted 25 November 2020;Published 1 March 2021
IAEES

Abstract
Simulation studies in population genetics play a crucial role in better understanding of different evolution scenarios and effects of different genetic models on genetic diversity. forward-in-time method starts with an initial population and follows the entire evolution under various genetic models within multiple generations. Artificial neural networks represent a formidable method for genetic simulation and prediction. In this study, we wanted to compare and corroborate results obtained with forward-in-time simulation with results attained from a specially designed strategy based on artificial neural networking. As input data, alleles of 13 microsatellite loci from 187 specimens representing autochthonous Adriatic haplotype of Salmo trutta L. from the Neretva River were used. The main goal of this study was to compare precision and reliability of these two methods. Our results are in concordance with other reports from literature which indicate that both of these approaches can be used as a reliable simulation tools. However, it is believed that artificial neural networks can represent more powerful simulation tools.

Keywords forward-in-time;artificial neural network;simulation;conservation.


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