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Advisor(s)
Abstract(s)
For this study a program was developed in Python on biological sequence alignment, considering the application of algorithms in the genetic analysis of Kristen rat sarcoma viral oncogene (KRAS) and its main mutations associated with cancer. The KRAS gene, like other genes in the same family, is responsible for encoding proteins that regulate cell proliferation, differentiation, and apoptosis. The algorithms employed include the Needleman-Wunsch algorithm as well as the Smith-Waterman algorithm and the Basic Local Alignment Search Tool (BLAST). The algorithms for multiple sequence alignment help to understand the function, evolution, and variability of biological sequences, significantly contributing to advances in genomics and proteomics. The objectives of this study are to apply algorithms for the effective alignment of biological sequences, compare the non-mutated KRAS sequence with principal mutations associated with cancer development, delineate and justify the selection of the algorithms used, assess their computational complexity, and facilitate 3D visualization of the sequences. Development of a program - BioAlign - in Python, with various functions including upload and visualization of sequences; use of different algorithms for global and local alignment; BLAST search; algorithms complexity analysis; obtaining the nucleotides positions; obtaining subsequence and its position; phylogenetic analysis; histogram visualization of sequence length and 3D structure visualization. The program is capable of analyzing and comparing the provided sequences using both local and global algorithms. The execution time among the three main algorithms differs, with the BLAST algorithm notably slower in returning results. This fact may be due to several factors, such as the complexity of the algorithm itself, the internet speed, and the response time of the NCBI website. The development of the BioAlign program indeed allows to address the proposed objectives. Furthermore, the completion of this project has enhanced proficiency in utilizing the Python programming language, demonstrating significant skill development.
Description
Keywords
Sequence alignment Algorithm KRAS
Pedagogical Context
Citation
Pereira, A. R., Lopes, C., Oliveira, C., Pereira, G., Moreira, R., & Faria, B. M. (2024). Sequence alignment: Comparative analysis of algorithms in KRAS genetic mutations. Proceedings of the 1st Symposium on Biostatistics and Bioinformatics Applied to Health, 25–26. https://recipp.ipp.pt/entities/publication/a634fd4f-6053-47fa-8145-4f876572cba7
Publisher
ESS | P. PORTO Edições
CC License
Without CC licence