NGPHYLO

Project funded by FCT (PTDC/CCI-BIO/29676/2017), from 01/10/2018 to 30/09/2021.

Abstract

The current ability to rapidly sequence whole microbial genomes is revolutionizing microbiology and epidemiological surveillance, with high impact on the identification of antimicrobial resistance genes and virulence factors which can have direct clinical application in the treatment of patients, or on the detection of outbreaks in hospital settings or in the food industry, e.g., by monitoring the spread of antimicrobial resistance, an ever growing concern. It has allowed also more complex phylogenetic analyses based on the whole genome data. The bottleneck has however shifted to data analysis problems. From a computational point of view, a growing concern is how algorithms and tools can be scaled up to analyse thousands of genetic loci in thousands of isolates. This project aims then to: (1) research and design efficient and scalable data structures and algorithms that allow phylogenetic analyses at large scales; (2) develop tools suitable for processing large scale phylogenetic analysis, deployable in cloud and HPC environments; (3) make tools available as reusable components, enabling the construction of more complex parametrizable pipeline workflows; (4) develop and integrate intuitive and user-friendly interfaces. The research team reflects the multidisciplinary character of the project. The team gathers researchers from two national research institutes, INESC-ID and IMM. Prior collaborations of this team in bioinformatics and computational biology focused on typing data analysis, phylogenetic inference and the development of software tools for these tasks.

Main topics

  1. Efficient and scalable algorithms for phylogenetic data analysis and processing.
  2. Population surveillance and outbreak detection.
  3. Modular platform for phylogenetic data integration, processing and visualization.

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