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Using this exploration and visualization interface, we utilize Data Science to uncover key insights within the healthcare landscape, particularly related to the sequences and metadata of pathogenic bacteria. Data science provides valuable insights into the large amount of internet data about individuals, institutions, and regulatory bodies, providing valuable understanding for decision-makers and healthcare professionals. The COVID-19 pandemic demonstrated its potential, establish essential evidence during emergencies. It emphasized the significance of data-driven approaches in dealing with complex and evolving public health crises, particularly those related to pathogens. By integrating sequence data and associating information, our platform provides a comprehensive understanding of pathogens present in the pulmonary environment. Through sophisticated visualization techniques, users can navigate and interpret complex metadata, gaining valuable perspectives on the intricate interplay between pathogens and health. This approach not only contributes to advancing scientific knowledge but also holds immense potential for shaping targeted strategies in the fight against infectious diseases. We selected nine bacterial genera that are reported in the literature as associated with the pathogenesis of the pulmonary environment.
This is the first version of the project and was fully developed by students and professors of Universidad Tecnologica Metropolitana. https://www.utem.cl/universidad/
Authors:
Fernanda Bravo Cornejo, bravoc@utem.cl; Diego Santibanez Oyarce, dsantibanezo@utem.cl; Camilo Cerda Sarabia, ccerdas@utem.cl; Hugo Osses Prado, hosses@utem.cl; Esteban Gomez Teran, egomez@utem.cl
Raul Caulier-Cisterna, rcaulier@utem.cl; Jorge Vergara-Quezada, jorgever@utem.cl; Ana Moya-Beltran, amoya@utem.cl (corresponding author).
This work was presented in the ‘1eras Jornadas de Ciencia de Datos y Salud pública’ organized by Escuela de Salud pública, Universidad de Chile. https://saludpublica.uchile.cl/extension/programas/1ras-jornadas-de-ciencia-de-datos-y-salud-publica/presentacion
Acknowledgement: Departamento de Informatica y Computacion, UTEM; Escuela de Informatica, UTEM; Laboratorio de Investigacion Aplicada, Departamento de Informatica y Computacion, UTEM.