Translational Bioinformatics (TBI) is defined as the union of translational medicine and bioinformatics. It emerges as a major advance in science and technology by covering everything, from the most basic database discoveries, to the development of algorithms for molecular and cellular analysis, as well as their clinical applications. This technology makes it possible to access the knowledge of scientific evidence and apply it to clinical practice. This manuscript aims to highlight the role of TBI in the study of complex diseases, as well as its application to the understanding and treatment of cancer. An integrative literature review was carried out, obtaining articles through several websites, among them: PUBMED, Science Direct, NCBI-PMC, Scientific Electronic Library Online (SciELO), and Google Academic, published in English, Spanish, and Portuguese, indexed in the referred databases and answering the following guiding question: “How does TBI provide a scientific understanding of complex diseases?” An additional effort is aimed at the dissemination, inclusion, and perpetuation of TBI knowledge from the academic environment to society, helping the study, understanding, and elucidating of complex disease mechanics and their treatment.

Precision and organization govern the cell cycle, ensuring normal proliferation. However, some cells may undergo abnormal cell divisions (neosis) or variations of mitotic cycles (endopolyploidy). Consequently, the formation of polyploid giant cancer cells (PGCCs), critical for tumor survival, resistance, and immortalization, can occur. Newly formed cells end up accessing numerous multicellular and unicellular programs that enable metastasis, drug resistance, tumor recurrence, and self-renewal or diverse clone formation. An integrative literature review was carried out, searching articles in several sites, including: PUBMED, NCBI-PMC, and Google Academic, published in English, indexed in referenced databases and without a publication time filter, but prioritizing articles from the last 3 years, to answer the following questions: (i) “What is the current knowledge about polyploidy in tumors?”; (ii) “What are the applications of computational studies for the understanding of cancer polyploidy?”; and (iii) “How do PGCCs contribute to tumorigenesis?”.

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Este artigo tem por objetivo fornecer um entendimento histórico acerca da biologia de sistemas, da mineração de texto, da curadoria manual, das redes biológicas, e, principalmente, das edes de interação proteína-proteína (redes PPIs). Ademais, este trabalho ainda busca traçar algumas bases para o desenvolvimento da construção das redes PPIs em diversos trabalhos acadêmicos (em variadas linhas de investigação), buscando o desenvolvimento de estudos computacionais (in silico) para um avanço sobre elucidações moleculares e celulares no que tange ao funcionamento proteico em inúmeras doenças, estados fisiológicos saudáveis e dentre outros focos de pesquisa. Assim, este tutorial está dividido em quatro partes: 1) Apresentação e explicação do tema: contexto histórico da Biologia de Sistemas, contexto histórico das Redes Biológicas, introdução e explicação sobre os componentes-chave das Redes de Interação Proteína-Proteína e Mineração de Texto; 2) Desenvolvimento do tutorial: exposição dos Componentes Necessários, da Busca de Artigos, da Seleção de Proteínas e da Construção da Rede; 3) Exposição conceitual sobre os dados obtidos: características da rede PPI, os Parâmetros Topológicos avaliados na rede PPI e a Avaliação Funcional da rede PPI; 4) Fornecimento de Literatura Complementar: visa à divulgação de outros materiais formativos úteis ao desenvolvimento do leitor;

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