{'fraction_non_alphanumeric': 0.014778325123152709, 'fraction_numerical': 0.0, 'mean_word_length': 5.663934426229508, '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}}
A technique to search for functional similarities in protein-protein interaction networks

We describe a method to search for similarities across protein-protein interaction networks of different organisms. The technique core consists in computing a maximum weight matching of bipartite graphs resulting from comparing the neighbourhoods of proteins belonging to different networks. Both quantitative and reliability information are exploited. We tested the method on the networks of S. cerevisiae, D. melanogaster and C. elegans. The experiments showed that the technique is able to detect functional orthologs when the sole sequence similarity does not prove itself sufficient. They also demonstrated the capability of our approach in discovering common biological processes involving uncharacterised proteins.