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Interpretable rule-based knowledge acquisition for characterizing fungal virulence factors

机译：基于可解释的规则的知识获取，用于表征真菌毒力因子

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摘要

Fungal virulence factors are molecules expressed and secreted by fungal pathogens that cause many serious diseases in plants and animals. Targeting virulence factors is helpful for vaccine development to combat fungal infections. However, few methods pay attention to characterize virulence factors and advance to understand their reverent functions. This study proposes a knowledge acquisition. method based on if-then rules for predicting fungal virulence factors (called FuVF). FuVF identifies nonvirulent and four types of virulence factors, adhesion, toxin, secretion, and biofilm by using top-ranked Gene Ontology terms (GO) with amino acid composition. The top-ranked GO terms are selected by according to their numbers of annotated proteins in the dataset. Based on these features, FuVF generates several if-then rules by using the decision tree mechanism for characterizing fungal virulence factors. The top-ranked informative rules with high certainty grades reveal that five terms and three amino acid compositions of T, Y and S are effective in distinguishing virulence factors in fungi. The five terms comprise GO:0009405 (pathogenesis), GO:0005886 (plasma membrane), GO:0006508 (proteolysis), GO:0016757 (transferase activity) and GO:0016021 (integral to membrane).
机译：真菌毒力因子是由真菌病原体表达和分泌的分子，导致植物和动物的许多严重疾病。针对毒力因子对疫苗开发有助于打击真菌感染。然而，很少有方法注意表征毒力因子并提前了解他们的虔诚功能。本研究提出了知识收购。基于IF-THE-THER规则的方法，用于预测真菌毒力因子（称为FUVF）。 Fuvf通过使用氨基酸组合物使用倒数排名基因本体论术语（GO）来鉴定非伏重和四种类型的毒力因子，粘附，毒素，分泌和生物膜。通过数据集中的标注蛋白数来选择排名级术语。基于这些特征，FUVF通过使用决策树机制来生成几种IF-DEN-DEL规则，用于表征真菌毒力因子。具有高确定性等级的排名级别的信息规则揭示了T，Y和S的五个术语和三种氨基酸组成，可有效地区分真菌中的毒力因子。五个术语包括Go：0009405（发病机制），GO：0005886（血浆膜），GO：0006508（蛋白水解），GO：0016757（转移酶活性）和GO：0016021（积分对膜）。

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