  Covid-19 infection, which spread to the whole world in December 2019 and is
still active, caused more than 250 thousand deaths in the world today.
Researches on this subject have been focused on analyzing the genetic structure
of the virus, developing vaccines, the course of the disease, and its source.
In this study, RNA sequences belonging to the SARS-CoV-2 virus are transformed
into gene motifs with two basic image processing algorithms and classified with
the convolutional neural network (CNN) models. The CNN models achieved an
average of 98% Area Under Curve(AUC) value was achieved in RNA sequences
classified as Asia, Europe, America, and Oceania. The resulting artificial
neural network model was used for phylogenetic analysis of the variant of the
virus isolated in Turkey. The classification results reached were compared with
gene alignment values in the GISAID database, where SARS-CoV-2 virus records
are kept all over the world. Our experimental results have revealed that now
the detection of the geographic distribution of the virus with the CNN models
might serve as an efficient method.
