Classification of Exon and Intron Regions on DNA Sequences with Hybrid Use of SBERT and ANFIS Approaches

Abstract

DNA is the part of the genome that contains enormous amounts of information related to life. Amino acids are formed by coding three nucleotides in this genome part, and the encoded amino acids are called codes in DNA. The frequency of the triple nucleotide in the DNA sequence allows for the evaluation of protein-coding (exon) and non-protein-coding (intron) regions. Distinguishing these regions enables the analysis of vital functions related to life. This study provides the classification of exon and intron regions for BCR-ABL and MEFV genes obtained from NCBI and Ensemble datasets, respectively. Then, existing DNA sequences are clustered using pretrained models in the scope of the SBERT approach. In the clustering process, K-Means and Agglomerative Clustering approaches are used consecutively. The frequency of repetition of codes is calculated with a representative sample selected from each cluster. The matrix is created using the frequencies of 64 different codons that constitute genetic code. This matrix is given as input to the ANFIS structure. The %88.88 accuracy rate is obtained with the ANFIS approach to classify exon and intron DNA sequences. As a result of this study, a successful result was produced independently of DNA length.

Keywords

• DNA sequences
• exon and intron regions
• K-Means and Agglomerative Clustering
• SBERT
• ANFIS

ANFIS ve SBERT Yaklaşımlarının Hibrit Kullanımı ile DNA Dizilimleri Üzerinde Ekson ve İntron Bölgelerinin Sınıflandırılması

Abstract

DNA, canlılığa ilişkin devasa bilgi barındıran genom parçasıdır. Bu genom parçasındaki üç nükleotidin kodlanması ile aminoasitler oluşur ve kodlanan aminoasitler DNA’da kod olarak isimlendirilir. DNA dizilimindeki üçlü nükleotidin frekansı, protein kodlayan(ekson) ve protein kodlamayan(intron) bölgelere ilişkin analiz imkanı sağlar. Bu bölgelerin ayırt edilmesi yaşama ilişkin hayati fonksiyonların değerlendirilmesini mümkün kılar. Bu çalışma sırasıyla NCBI ve Ensemble veri setlerinden elde edilen BCR-ABL ve MEFV genleri için ekson ve intron bölgelerinin sınıflandırılmasını sağlamıştır. Ardından SBERT yaklaşımı kapsamında önceden eğitilmiş modeller ile mevcut DNA dizilimleri kümelenmiştir. Kümeleme sürecinde K-Means ve Agglomerative Kümeleme yaklaşımları art arda kullanılmıştır. Her bir kümeden seçilen temsili bir örnek ile kodonların tekrarlanma sıklığı hesaplanmıştır. Genetik kodun oluşmasını sağlayan 64 farklı kodonların frekansı kullanılarak matris oluşturulmuştur. Bu matris ANFIS yapısına girdi olarak verilmiştir. ANFIS yaklaşımı ile ekson ve intron bölgelerinin sınıflandırılmasında %88.88 doğruluk oranı elde edilmiştir. Bu çalışmanın sonucunda DNA uzunluğundan bağımsız başarılı bir sonuç üretilmiştir.

Keywords

• DNA sequences
• exon and intron regions
• K-Means and Agglomerative Clustering
• SBERT
• ANFIS

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