Chromosomes, which are formed by the combination of DNA and special proteins, are structures that can show some changes with the effect of genetic or environmental factors. The DNA molecule in these structures carries vital information in elucidating critical information about life. DNA, which is formed by the combination of sugar, phosphate and organic bases, has exon and intron regions separation. Information about the processes in the life cycle of cells, the changes experienced by stem cells, the regulations in the growth and development stage, the development status of cancer, mutation occurrences and protein synthesis are stored in exon regions. Distinguishing exon regions that form 3% of a cell's DNA is challenging. However, detecting diseases on genetically based facts offers more precise outputs. For this reason, analyses were made on the BCR-ABL gene and BRCA-1 mutation carrier genes to analyse leukemia and breast cancer, which are genetically based diseases. First, these genes obtained from the NCBI gene bank were digitized by integer mapping technique. The digitized sequences were given as input to the hash function. This proposed hash function consists of the steps of finding the logarithmic equivalent of the total number of digitized organic bases, summing all logarithmic equivalents, rounding to the nearest integer, expressing it in binary and placing it in the hash table. These outputs, which define the exon and intron regions, were shown as clusters to find the new input region easily. The collision cluster is the binary representation of key values representing both exon and intron regions for the same region. The main goal is to have a small number of elements in this cluster. With the proposed hierarchy in this study, only one collision occurred for BCR-ABL and BRCA-1 genes. Accuracy rates of the proposed approach based on a mathematical basis and independent of nucleotide length were obtained 93.33%, and 96%, respectively.
Primary Language | English |
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Subjects | Engineering |
Journal Section | Research Articles |
Authors | |
Publication Date | September 30, 2023 |
Submission Date | April 11, 2023 |
Published in Issue | Year 2023 Issue: 054 |