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作者机构: Concordia University Canada McGill University McGill Genome Center Majewski Lab Canada Brazil DEXL National Laboratory for Scientific Computing Brazil Department of Oncology-Pathology Center for Molecular Medicine Karolinska Institutet Sweden Algorithmic Dynamics Lab Karolinska Institutet Sweden School of Biomedical Engineering and Imaging Sciences King's College London United Kingdom
出 版 物:《arXiv》 (arXiv)
年 卷 期:2022年
核心收录:
摘 要: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. Copyright © 2022, The Authors. All rights reserved.