Prediction of detectable peptides in MS data using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Ahmed:2014:GECCOcomp,
  author =       "Soha Ahmed and Mengjie Zhang and Lifeng Peng",
  title =        "Prediction of detectable peptides in MS data using
                 genetic programming",
  booktitle =    "GECCO Comp '14: Proceedings of the 2014 conference
                 companion on Genetic and evolutionary computation
                 companion",
  year =         "2014",
  editor =       "Christian Igel and Dirk V. Arnold and 
                 Christian Gagne and Elena Popovici and Anne Auger and 
                 Jaume Bacardit and Dimo Brockhoff and Stefano Cagnoni and 
                 Kalyanmoy Deb and Benjamin Doerr and James Foster and 
                 Tobias Glasmachers and Emma Hart and Malcolm I. Heywood and 
                 Hitoshi Iba and Christian Jacob and Thomas Jansen and 
                 Yaochu Jin and Marouane Kessentini and 
                 Joshua D. Knowles and William B. Langdon and Pedro Larranaga and 
                 Sean Luke and Gabriel Luque and John A. W. McCall and 
                 Marco A. {Montes de Oca} and Alison Motsinger-Reif and 
                 Yew Soon Ong and Michael Palmer and 
                 Konstantinos E. Parsopoulos and Guenther Raidl and Sebastian Risi and 
                 Guenther Ruhe and Tom Schaul and Thomas Schmickl and 
                 Bernhard Sendhoff and Kenneth O. Stanley and 
                 Thomas Stuetzle and Dirk Thierens and Julian Togelius and 
                 Carsten Witt and Christine Zarges",
  isbn13 =       "978-1-4503-2881-4",
  keywords =     "genetic algorithms, genetic programming, biological
                 and biomedical applications: Poster",
  pages =        "37--38",
  month =        "12-16 " # jul,
  organisation = "SIGEVO",
  address =      "Vancouver, BC, Canada",
  URL =          "http://doi.acm.org/10.1145/2598394.2598421",
  DOI =          "doi:10.1145/2598394.2598421",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "The use of mass spectrometry to verify and quantify
                 biomarkers requires the identification of the peptides
                 that can be detectable. In this paper, we propose the
                 use of genetic programming (GP) to measure the
                 detection probability of the peptides. The new GP
                 method is tested and verified on two different yeast
                 data sets with increasing complexity and shows improved
                 performance over other state-of-art classification and
                 feature selection algorithms.",
  notes =        "Also known as \cite{2598421} Distributed at
                 GECCO-2014.",
}

Genetic Programming entries for Soha Ahmed Mengjie Zhang Lifeng Peng

Citations