Department of Physics and Psychology (Alumni), Concordia University, Montreal, Canada.
McGill University, McGill Genome Center, Majewski Lab, Montreal, Canada.
NPJ Syst Biol Appl. 2024 Aug 7;10(1):82. doi: 10.1038/s41540-024-00403-y.
We demonstrate that the assembly pathway method underlying assembly theory (AT) is an encoding scheme widely used by popular statistical compression algorithms. We show that in all cases (synthetic or natural) AT performs similarly to other simple coding schemes and underperforms compared to system-related indexes based upon algorithmic probability that take into account statistical repetitions but also the likelihood of other computable patterns. Our results imply that the assembly index does not offer substantial improvements over existing methods, including traditional statistical ones, and imply that the separation between living and non-living compounds following these methods has been reported before.
我们证明了组装理论(AT)所基于的组装途径方法是一种广泛应用于流行的统计压缩算法的编码方案。我们表明,在所有情况下(合成的或自然的),AT 的表现与其他简单的编码方案相似,并且不如基于算法概率的系统相关索引表现好,这些索引考虑了统计重复,但也考虑了其他可计算模式的可能性。我们的结果表明,组装指标并没有比现有的方法,包括传统的统计方法,提供实质性的改进,并表明这些方法中生物和非生物化合物的分离之前已经有报道。