{"publication_status":"published","publist_id":"2461","type":"journal_article","citation":{"ista":"Kupczok A, Dittrich P. 2006. Determinants of simulated RNA evolution. Journal of Theoretical Biology. 238(3), 726–35.","mla":"Kupczok, Anne, and Peter Dittrich. “Determinants of Simulated RNA Evolution.” <i>Journal of Theoretical Biology</i>, vol. 238, no. 3, Elsevier, 2006, pp. 726–35, doi:<a href=\"https://doi.org/10.1016/j.jtbi.2005.06.019\">10.1016/j.jtbi.2005.06.019</a>.","apa":"Kupczok, A., &#38; Dittrich, P. (2006). Determinants of simulated RNA evolution. <i>Journal of Theoretical Biology</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.jtbi.2005.06.019\">https://doi.org/10.1016/j.jtbi.2005.06.019</a>","chicago":"Kupczok, Anne, and Peter Dittrich. “Determinants of Simulated RNA Evolution.” <i>Journal of Theoretical Biology</i>. Elsevier, 2006. <a href=\"https://doi.org/10.1016/j.jtbi.2005.06.019\">https://doi.org/10.1016/j.jtbi.2005.06.019</a>.","ama":"Kupczok A, Dittrich P. Determinants of simulated RNA evolution. <i>Journal of Theoretical Biology</i>. 2006;238(3):726-735. doi:<a href=\"https://doi.org/10.1016/j.jtbi.2005.06.019\">10.1016/j.jtbi.2005.06.019</a>","ieee":"A. Kupczok and P. Dittrich, “Determinants of simulated RNA evolution.,” <i>Journal of Theoretical Biology</i>, vol. 238, no. 3. Elsevier, pp. 726–35, 2006.","short":"A. Kupczok, P. Dittrich, Journal of Theoretical Biology 238 (2006) 726–35."},"publisher":"Elsevier","publication":"Journal of Theoretical Biology","month":"01","volume":238,"extern":1,"date_published":"2006-01-01T00:00:00Z","abstract":[{"text":"Models of RNA secondary structure folding are widely used to study evolution in theory and simulation. However, systematic studies of the parameters involved are rare. In this paper, we study by simulation how RNA evolution is influenced by three different factors, namely the mutation rate, scaling of the fitness function, and distance measure. We found that for low mutation rates the qualitative evolutionary behavior is robust with respect to the scaling of the fitness function. For efficient mutation rates, which are close to the error threshold, scaling and distance measure have a strong influence on the evolutionary behavior. A global distance measure that takes sequence information additively into account lowers the error threshold. When using a local sequence-structure alignment for the distance, we observed a smoother evolution of the fitness over time. Finally, in addition to the well known error threshold, we identify another threshold of the mutation rate, called divergence threshold, where the qualitative transient behavior changes from a localized to an exploratory search.","lang":"eng"}],"status":"public","date_updated":"2021-01-12T07:52:03Z","date_created":"2018-12-11T12:05:03Z","author":[{"full_name":"Anne Kupczok","last_name":"Kupczok","id":"2BB22BC2-F248-11E8-B48F-1D18A9856A87","first_name":"Anne"},{"first_name":"Peter","last_name":"Dittrich","full_name":"Dittrich,Peter"}],"title":"Determinants of simulated RNA evolution.","_id":"3767","year":"2006","day":"01","issue":"3","page":"726 - 35","intvolume":"       238","quality_controlled":0,"doi":"10.1016/j.jtbi.2005.06.019"}