- author = "Jin-Wu Nam and Je-Gun Joung and Young-Sirk Ahn and Byoung-Tak Zhang",
- title = "Two-Step Genetic Programming for Optimization of {RNA} Common-Structure",
- booktitle = "Applications of Evolutionary Computing, EvoWorkshops2004: {EvoBIO}, {EvoCOMNET}, {EvoHOT}, {EvoIASP}, {EvoMUSART}, {EvoSTOC}",
- year = "2004",
- month = "5-7 " # apr,
- editor = "Guenther R. Raidl and Stefano Cagnoni and Jurgen Branke and David W. Corne and Rolf Drechsler and Yaochu Jin and Colin R. Johnson and Penousal Machado and Elena Marchiori and Franz Rothlauf and George D. Smith and Giovanni Squillero",
- series = "LNCS",
- volume = "3005",
- address = "Coimbra, Portugal",
- publisher = "Springer Verlag",
- publisher_address = "Berlin",
- pages = "73--83",
- keywords = "genetic algorithms, genetic programming, evolutionary computation",
- ISBN = "3-540-21378-3",
-
URL = "
http://bi.snu.ac.kr/Publications/Journals/International/LNCS_3005_73-83(2004).pdf",
-
DOI = "
10.1007/978-3-540-24653-4_8",
- abstract = "We present an algorithm for identifying putative ncRNAs using an RCSG (RNA Common Structural Grammar) and show the effectiveness of the algorithm. The algorithm consists of two steps: structure learning step and sequence learning step. Both steps are based on genetic programming. Generally genetic programming has been applied to learn programs automatically, reconstruct networks, and predict protein secondary structures. In this study, we have applied genetic programming to optimise structural grammars. The structural grammars can be formulated by some rules as tree structure including function variables. They can be learned by genetic programming. We have defined the rules on how structure definition grammars can be encoded into function trees. The results we obtained from the experiments with RCSG of tRNA and 5S small rRNA and demonstrate the efficiency of our algorithm.",
-
notes = "EvoWorkshops2004
esRCSG used in \cite{Nam:2005:NAR}",
