{'fraction_non_alphanumeric': 0.011363636363636364, 'fraction_numerical': 0.0, 'mean_word_length': 5.782051282051282, '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': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Development and performance evaluation of FLANN based model for protein structural class prediction

During last few decades' accurate prediction of protein structural class has been a challenging problem. Efficient and meaningful representation of protein molecule plays a significant role. In this paper Chou's pseudo amino acid composition along with amphiphillic correlation factor has been used to represent protein data. A simple functionally linked artificial neural network has been used for structural class prediction.