A Dynamic Method and Program for Disease-Based Genetic Classification of Individuals

Year 2023, , 12 - 20, 10.03.2024

Onur Çakırgöz , Süleyman Sevinç

https://doi.org/10.57020/ject.1375605

Abstract

Personalized medicine is gaining increasing importance. However, genetic-based diseases have different underlying genetic factors, requiring separate relative risk models for each disease. In addition to these difficulties, comparing individuals according to their genetic characteristics and determining a personalized treatment method based on this, is a separate problem which is very difficult to do manually. In this study, a dynamic classification method and program is proposed for disease-based classification of individuals according to their genetic characteristics. To the best of our knowledge, this is the first generic method which performs disease-based classification of individuals. In the developed program, relative risk models containing only genetic factors are an input of the program and a common format has been created for this purpose. Our generic classification method classifies people by using information from any relative risk model rearranged according to the common format. Thanks to this program, relative risk models can be managed from a single point, many people can be classified based on their genetic characteristics, and individuals, who are genetically most similar to any person, can be determined by experts using the outputs (relevant tables) of the program.

Keywords

personalized medicine, computational medicine, genetic classification, relative risk model, genetic similarity, genetic variation

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