{"title":"Central Dogma of Molecular Biology - New Paradigm in Evolutionary Computation","authors":"C. Rotar","doi":"10.1109/SYNASC.2014.46","DOIUrl":null,"url":null,"abstract":"The aim of this study is to develop a new evolutionary computation paradigm in terms of molecular biology. Standard genetic algorithms are heuristics inspired by the simplified model of natural evolution and genetics. The latest discoveries and innovations from molecular biology, related to the conventional central dogma of molecular biology, generate the necessity of updating the genetic algorithms, although successfully applied in various complex tasks. In this direction, the research in Evolutionary Computation requires a reconsideration of the concepts and theories underlying the development of these popular optimization techniques. Since the emergence of the new features is important in the evolution, the DNA code requires progress. Evolutionary Computation which is based on the mutation and the natural selection can be reconsidered in terms of protein synthesis and reverse transcription. From the computational perspective, a biological phenomenon might be interpreted in various forms in order to obtain reliable computational techniques.","PeriodicalId":150575,"journal":{"name":"2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYNASC.2014.46","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
The aim of this study is to develop a new evolutionary computation paradigm in terms of molecular biology. Standard genetic algorithms are heuristics inspired by the simplified model of natural evolution and genetics. The latest discoveries and innovations from molecular biology, related to the conventional central dogma of molecular biology, generate the necessity of updating the genetic algorithms, although successfully applied in various complex tasks. In this direction, the research in Evolutionary Computation requires a reconsideration of the concepts and theories underlying the development of these popular optimization techniques. Since the emergence of the new features is important in the evolution, the DNA code requires progress. Evolutionary Computation which is based on the mutation and the natural selection can be reconsidered in terms of protein synthesis and reverse transcription. From the computational perspective, a biological phenomenon might be interpreted in various forms in order to obtain reliable computational techniques.