New SDC function prediction based on protein-protein interaction using bioinformatics tools

Autor(es)

Zandonadi, Flavia S. ^[1] ; Santa Cruz, Elisa Castaneda ^[1] ; Korvala, Johanna ^{[2, 3]}

Afiliação do(s) autor(es)

^[1] Univ Estadual Campinas, Dept Quim Analit, Lab Bioanalyt & Integrated Omics LaBIOmics, UNICAMP, Campinas, SP - Brazil

^[2] Univ Oulu, Bioctr Oulu, Canc & Translat Med Res Unit, Oulu - Finland

^[3] Univ Oulu, Fac Med, Oulu - Finland

• Tipo de documento: Artigo de Revisão
• Fonte: COMPUTATIONAL BIOLOGY AND CHEMISTRY; v. 83, DEC 2019.
• Citações Web of Science: 1

Resumo

The precise roles for SDC have been complex to specify. Assigning and reanalyzing protein and peptide identification to novel protein functions is one of the most important challenges in postgenomic era. Here, we provide SDC molecular description to support, contextualize and reanalyze the corresponding protein-protein interaction (PPI). From SDC-1 data mining, we discuss the potential of bioinformatics tools to predict new biological rules of SDC. Using these methods, we have assembled new possibilities for SDC biology from PPI data, once, the understanding of biology complexity cannot be capture from one simple question. (AU)

• Processo FAPESP: 13/02257-9 - Busca de ligantes do sindecam-1 utilizando abordagem de proteômica quantitativa
• Beneficiário: Flávia da Silva Zandonadi
• Modalidade de apoio: Bolsas no Brasil - Doutorado