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原文連結
論文資訊
- 類型：已發表論文
- 日期：2021-08-17
摘要
Background Best match graphs (BMGs) are a class of colored digraphs that naturally appear in 數學 系統發育s as a representation of the pairwise most closely related genes among multiple 物種. An arc connects a gene x with a gene y from another 物種 (vertex color) Y whenever it is one of the 系統發育ally closest relatives of x. BMGs can be approximated with the help of similarity measures between gene sequences, albeit not without errors. Empirical estimates thus will usually violate the theoretical properties of BMGs. The corresponding graph editing problem can be used to guide error correction for best match data. Since the arc set modification problems for BMGs are NP-complete, efficient heuristics are needed if BMGs are to be used for the practical analysis of 生物 sequence data. Results Since BMGs hav
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