工作流程
计算生物学
基因组
基因
生物
相似性(几何)
生物信息学
遗传学
计算机科学
数据库
人工智能
图像(数学)
作者
Jorge C. Navarro-Muñoz,Jérôme Collemare
标识
DOI:10.1007/978-1-0716-2273-5_1
摘要
Predicting secondary metabolite biosynthetic gene clusters is a routine analysis performed for each newly sequenced fungal genome. Yet, the usefulness of such predictions remains restricted as they provide total numbers of biosynthetic pathways with only very limited biological significance. In this chapter, we describe a workflow to predict and analyze biosynthetic gene clusters in fungal genomes. It relies on similarity networking and phylogeny to perform genetic dereplication and to prioritize candidate gene clusters that potentially produce new compounds. This basic workflow includes the generation of high-quality figures for publication.
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