Bioinformatics and Artificial
Intelligence approach
Bioinformatics and Artificial intelligence (AI) are used to understand biological data and development of algorithms and systems that learn from data and can make predictions or decisions based on this information. In the field of biology, AI is used to analyze complex patterns in large data sets, helping to identify relationships that may not be immediately apparent. The integration of bioinformatics with AI has generated significant advances in science, enabling discoveries that can transform and understand the biological world. In this context, bioinformatics will contribute with omics analysis and artificial intelligence to develop identifying aspects that enable comparisons between subgroups of microorganisms and biodiversity analysis within the various partner collections.
Objectives
1
Develop new technologies for data analysis and pattern recognition on a genomic and metagenomic scale, using artificial intelligence to study microbiological characteristics and prospect species present in collections.
2
​Establish markers for in silico tracking of resistance and virulence genes.
3
Compare the genetic profile of strains of disease-causing agents in humans with isolates from the environment and animals, aiming to elucidate environmental niches and infection routes through bioinformatics, molecular markers, genomic sequencing, transcriptome analyses, and haplotyping.
4
Develop new data mining and pattern recognition technologies to be applied on genomic and metagenomic scales.
5
Explore public data covering microorganisms of interest through artificial intelligence for determination and vector formatting, enabling visualization, regional compositions, and support for microorganism prospecting in collections.
6
Develop artificial intelligence to study the characteristics of collections in broad aspects that allow comparisons between microorganism subgroups and biodiversity analyses.