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Sequence alignment: Comparative analysis of algorithms in KRAS genetic mutations

dc.contributor.authorPereira, Ana Rita
dc.contributor.authorLopes, Carlos
dc.contributor.authorOliveira, Catarina
dc.contributor.authorPereira, Gonçalo
dc.contributor.authorMoreira, Rui
dc.contributor.authorFaria, Brígida Mónica
dc.contributor.authorFaria, Brigida Monica
dc.date.accessioned2025-11-18T14:41:08Z
dc.date.available2025-11-18T14:41:08Z
dc.date.issued2025-04-14
dc.description.abstractFor 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.por
dc.identifier.citationPereira, 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
dc.identifier.isbn978-989-9045-35-4
dc.identifier.urihttp://hdl.handle.net/10400.22/30968
dc.language.isoeng
dc.peerreviewedn/a
dc.publisherESS | P. PORTO Edições
dc.relation.hasversionhttps://recipp.ipp.pt/entities/publication/a634fd4f-6053-47fa-8145-4f876572cba7
dc.rights.uriN/A
dc.subjectSequence alignment
dc.subjectAlgorithm
dc.subjectKRAS
dc.titleSequence alignment: Comparative analysis of algorithms in KRAS genetic mutationspor
dc.typeconference poster
dspace.entity.typePublication
oaire.citation.conferenceDate2024-05-03
oaire.citation.conferencePlacePorto
oaire.citation.endPage26
oaire.citation.startPage25
oaire.citation.titleProceedings of the 1st Symposium on Biostatistics and Bioinformatics Applied to Health
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameFaria
person.givenNameBrigida Monica
person.identifierR-000-T1F
person.identifier.ciencia-id0D1F-FB5E-55E4
person.identifier.orcid0000-0003-2102-3407
person.identifier.ridC-6649-2012
person.identifier.scopus-author-id6506476517
relation.isAuthorOfPublication85832a40-7ef9-431a-be0c-78b45ebbae86
relation.isAuthorOfPublication.latestForDiscovery85832a40-7ef9-431a-be0c-78b45ebbae86

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