Pato: prediction of probiotic bacteria using metabolic features
Rafaella Sinnott Dias1, Daniela Peres Martinez1, Fábio Pereira Leivas Leite1
1Laboratório de Bioinformática OmixLab, Centro de Desenvolvimento Tecnológico, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Brazil.
Abstract:
Probiotics have gained recognition for their health-promoting benefits, particularly in the gastrointestinal and immunological systems. Among promising probiotic candidates, Lactobacillus strains, belonging to the lactic acid bacteria (LAB) group, play a significant role in human microbiota. To aid in the in silico identification of Lactobacillus strains with probiotic potential, this study presents a novel classification approach based on functional and metabolism-related elements, which offers improved accuracy and explainability compared to traditional k-mer-based methods. By considering the functional characteristics of genomic sequences, this approach contributes to a clearer understanding of the traits associated with probiotic activity, facilitating the selection of strains with optimal health-promoting attributes. The webserver is available at http://200.132.101.156:5001/ .
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