Data Mining for Identification of Forkhead Box O (FOXO۳a) in Different Organisms Using Nucleotide and Tandem Repeat Sequences

Background: Deregulation of FOXO۳a gene which belongs to Forkhead box O (FOXO) transcription factors, can cause cancer (e.g. breast cancer). FOXO factors have important role in ubiquitination, acetylation, de-acetylation, protein-protein interactions and phosphorylation. Understanding the regulation and mechanisms of FOXO۳a can lead to cancer treatment. The aim of this study recent association of data mining with genetics has provided a strong tool for knowledge discovery. Materials and Methods: Using genetics and bioinformatics, ۳۰ sequences of FOXO۳a genes were extracted from different species and were used in two datasets including ۶۵ nucleotide features and ۵۱ tandem repeat sequences. Then, we used different feature weighting and decision tree data mining algorithms on these datasets. Results: Among nucleotide features, the frequency of AA dinucleotide was the most important genomic feature for FOXO۳a gene identification. Among tandem repeat sequences, the strings of TTTTTTTTT, GAGGAGGAG, CGGCGGCGGCGG and CGGCGGCGGCGGCGG were the most effective ones to distinguish FOXO۳A gene between different species. Conclusion: The results of this study are important in understanding FOXO۳a gene and developing a pathway for cancer and gene therapies in humans.

کلیدواژه ها:

Decision tree ، Data mining ، Rapidminer ، Forkhead box O۳