{'fraction_non_alphanumeric': 0.013972055888223553, 'fraction_numerical': 0.003992015968063872, 'mean_word_length': 5.275, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
An automatized topological method to test a priori global identifiability of a class of compartmental models

The paper deals with a priori global identifiability of compartmental models of biological systems. We propose an automatized topological method to test a priori global identifiability of a class of linear compartmental models of relatively large order (n≤ 10). The class is defined by some structural constraints but is sufficiently general to warrant automation. A case study is presented.