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Interpreting k-mer–based signatures for antibiotic resistance prediction
Author(s) -
Magali Jaillard,
Mattia Palmieri,
Alex van Belkum,
Pierre Mahé
Publication year - 2020
Publication title -
gigascience
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 2.947
H-Index - 54
ISSN - 2047-217X
DOI - 10.1093/gigascience/giaa110
Subject(s) - antibiotic resistance , computer science , computational biology , antibiotics , data science , biology , microbiology and biotechnology
Recent years have witnessed the development of several k-mer-based approaches aiming to predict phenotypic traits of bacteria on the basis of their whole-genome sequences. While often convincing in terms of predictive performance, the underlying models are in general not straightforward to interpret, the interplay between the actual genetic determinant and its translation as k-mers being generally hard to decipher.

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