Before revision:  The measures reveal the known in vivo versus in vitro predictive discrepancies , but they also uncover the internal structure of G and C within the nucleosome length , thus disclosing more than simply GC content when one examines alphabet transformations that separate and scramble the GC content signal and the DNA sequence . Most current prediction methods are based upon training (e.g. k-mer discovery), the one here advanced, however, is a training-free approach to investigating informative measures of DNA information content in connection with structural nucleosomic packing .
After revision:  The measures reveal the known in vivo versus in vitro predictive discrepancies , but they also uncover the internal structure of G and C within the nucleosome length and find that complexity indices are informative of nucleosome occupancy. We compare against the gold standard (Kaplan model) and find similar and complementary results with the main difference that our sequence complexity approach. For example, for high occupancy, complexity-based scores outperform the Kaplan model for predicting binding representing a significant advancement in predicting the highest nucleosome occupancy following a training-free approach to investigating informative measures of DNA information content in connection with structural nucleosomic packing .