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Interpreting k-mer–based signatures for antibiotic resistance prediction
GigaScience ( IF 11.8 ) Pub Date : 2020-10-17 , DOI: 10.1093/gigascience/giaa110 Magali Jaillard 1 , Mattia Palmieri 1 , Alex van Belkum 1 , Pierre Mahé 1
GigaScience ( IF 11.8 ) Pub Date : 2020-10-17 , DOI: 10.1093/gigascience/giaa110 Magali Jaillard 1 , Mattia Palmieri 1 , Alex van Belkum 1 , Pierre Mahé 1
Affiliation
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.
中文翻译:
解释基于 k-mer 的抗生素耐药性预测签名
近年来,一些基于k聚体的方法得到了发展,旨在根据细菌的全基因组序列来预测细菌的表型特征。虽然在预测性能方面通常令人信服,但底层模型通常不容易解释,实际遗传决定因素与其翻译为k聚体之间的相互作用通常难以破译。
更新日期:2020-10-17
中文翻译:
解释基于 k-mer 的抗生素耐药性预测签名
近年来,一些基于k聚体的方法得到了发展,旨在根据细菌的全基因组序列来预测细菌的表型特征。虽然在预测性能方面通常令人信服,但底层模型通常不容易解释,实际遗传决定因素与其翻译为k聚体之间的相互作用通常难以破译。