Evolving Regular Expression-based Sequence Classifiers for Protein Nuclear Localisation

Created by W.Langdon from gp-bibliography.bib Revision:1.8010

@InProceedings{heddad:evows04,

• author = "Amine Heddad and Markus Brameier and Robert M. MacCallum",
• title = "Evolving Regular Expression-based Sequence Classifiers for Protein Nuclear Localisation",
• 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 = "31--40",
• keywords = "genetic algorithms, genetic programming, evolutionary computation, perl, grammar, BNF, linear GP, LGP, RE, regular expressions",
• ISBN = "3-540-21378-3",
• URL = "http://www.sbc.su.se/~maccallr/publications/heddad-evobio2004.pdf",
• DOI = "doi:10.1007/978-3-540-24653-4_4",
• abstract = "A number of bioinformatics tools use regular expression (RE) matching to locate protein or DNA sequence motifs that have been discovered by researchers in the laboratory. For example, patterns representing nuclear localisation signals (NLSs) are used to predict nuclear localisation. NLSs are not yet well understood, and so the set of currently known NLSs may be incomplete. Here we use genetic programming (GP) to generate RE-based classifiers for nuclear localisation. While the approach is a supervised one (with respect to protein location), it is unsupervised with respect to already known NLSs. It therefore has the potential to discover new NLS motifs. We apply both tree based and linear GP to the problem. The inclusion of predicted secondary structure in the input does not improve performance. Benchmarking shows that our majority classifiers are competitive with existing tools. The evolved REs are usually NLS like and work is underway to analyse these for novelty.",
• notes = "EvoWorkshops2004, perlGP, grammar (not needed, cf p39?). Broken Dec 2021 http://www.sbc.su.se/~maccallr/nucpred/ perl eval(), grammar, stgp, matches(),, pdiv, plog, multiple classifier combination majority vote. 'No crossover is allowed between REs' p38. Removing ineffective code. 'LGP very close to PerlGP' p38. RE matching done in C. cf. \cite{brameier:nucpred}",

}

Genetic Programming entries for Amine Heddad Markus Brameier Robert M MacCallum

Citations