In this work we explore the dissimilarity between symmetric word pairs, by comparing the inter-word distance distribution of a word to that of its reversed complement. We propose a new measure of dissimilarity between such distributions. Since symmetric pairs with different patterns could point to evolutionary features, we search for the pairs with the most dissimilar behaviour. We focus our study on the complete human genome and its repeat-masked version.
|Nome||Advances in Intelligent Systems and Computing|
|Conferência||11th International Conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2017|
|Período||21/06/17 → 23/06/17|