A New Data Modeling Approach for Alignment-free Biological Applications

  • Diogo Munaro Vieira Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio)
  • Elvismary Molina de Armas Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio) https://orcid.org/0000-0002-0606-5994
  • Maria L. G. Jaramillo Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio) https://orcid.org/0000-0001-6649-9738
  • Marcos Catanho Fundação Oswaldo Cruz (Fiocruz)
  • Antonio B. Miranda Fundação Oswaldo Cruz (Fiocruz)
  • Edward Hermann Haeusler Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio)
  • Sérgio Lifschitz Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio)

Resumo


Encontrar proteínas homólogas e agrupá-las são tarefas de extrema importância para a biologia, que atualmente conta com ferramentas baseadas em informações do DNA ou das sequências de aminoácidos dessas proteínas. Essas tarefas exigem a identificação de padrões evolutivos que são difíceis de obter automaticamente usando métodos tradicionais. Este trabalho propõe uma abordagem de modelagem de dados para alavancar padrões evolutivos em tarefas de busca, classificação e agrupamento de homólogos por meio de um processo alignment-free usando algoritmos de similaridade de imagem. Essa estratégia é valiosa mesmo para homólogos distantes e contribui para a privacidade e segurança dos dados.

Palavras-chave: Data Modeling, Molecular Biology, Homologous Protein, Feature Representation, Computer Vision, Human Visual System, Machine Learning Explainability, Data Masking, Data Privacy

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Publicado
25/09/2023
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VIEIRA, Diogo Munaro; DE ARMAS, Elvismary Molina; JARAMILLO, Maria L. G.; CATANHO, Marcos; MIRANDA, Antonio B.; HAEUSLER, Edward Hermann; LIFSCHITZ, Sérgio. A New Data Modeling Approach for Alignment-free Biological Applications. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 38. , 2023, Belo Horizonte/MG. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 1-13. ISSN 2763-8979. DOI: https://doi.org/10.5753/sbbd.2023.232471.