{'fraction_non_alphanumeric': 0.014238773274917854, 'fraction_numerical': 0.0, 'mean_word_length': 5.671532846715328, '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}}
Protein Evolution as a Parallel-distributed Process: A Novel Approach to Evolutionary Modeling and Protein Design

Proteins are complex adaptive systems. Their functional and structural units, termed domains, are conserved and recombined during evolution. Domains are thermodynamically stable and fold independently within the context of the whole protein, and can arguably be seen as stable units of evolution. New domain functions evolve within the constraints of maintaining thermodynamic stability and autonomous folding capability. This gives rise to a complex interplay of molecular organization and evolutionary dynamics, which is still a largely unexplored area of research. The major aim of this paper is to approach this problem from a perspective informed by recent developments in complexity theory. This work employs distributed representation by neural networks in modeling protein domain evolution.