TY - JOUR T1 - Efficient Algorithms for Probing the RNA Mutation Landscape A1 - Waldispühl, Jérôme A1 - Devadas, Srinivas A1 - Berger, Bonnie A1 - Clote, Peter Y1 - 2008/08/08 N2 - Author Summary Evolution is a central concept in biology. This phenomenon can be observed at all levels of the organization of life—from single molecules to multicellular organisms. Here, we focus our attention on the implication of evolution at the level of nucleic acid sequences. In this context, RNA sequences presumably have been optimized by evolution to achieve specific functions. These functions are supported by a structure that can be determined using thermodynamics-based models and energy minimization techniques. In this work, we develop efficient algorithms for predicting energetically favorable mutations and study their impact on the stability of the structure. We use these techniques to reveal sequences under evolutionary pressure and design new methods to predict lethal mutations. Applications of our tool lead to a better understanding of the mutational process of some key regulatory elements of two important pathogenic RNA viruses—human immunodeficiency virus and hepatitis C virus. JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 4 IS - 8 UR - https://doi.org/10.1371/journal.pcbi.1000124 SP - e1000124 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1000124 ER -