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Comparison of commercially available genetic algorithms: GAs as variable selection tool

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Abstract

Many commercially available software programs claim similar efficiency and accuracy as variable selection tools. Genetic algorithms are commonly used variable selection methods where most relevant variables can be differentiated from ‘less important’ variables using evolutionary computing techniques. However, different vendors offer several algorithms, and the puzzling question is: which one is the appropriate method of choice? In this study, several genetic algorithm tools (e.g. GFA from Cerius2, QuaSAR-Evolution from MOE and Partek’s genetic algorithm) were compared. Stepwise multiple linear regression models were generated using the most relevant variables identified by the above genetic algorithms. This procedure led to the successful generation of Quantitative Structure–activity Relationship (QSAR) models for (a) proprietary datasets and (b) the Selwood dataset.

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References

  • C. Hansch A.R. Steward (1964) J. Med. Chem., 44 691

    Google Scholar 

  • C. Hansch R.M. Muir T. Fujita P.P. Maloney F. Geiger M. Streich (1963) J. Am. Chem. Soc., 85 1817

    Google Scholar 

  • G.M. Keseru (2003) Mol. Div., 7 1

    Google Scholar 

  • U. Norinder T. Hogberg (2002) Textbook of Drug Design and Discovery Taylor & Francis New York, NY

    Google Scholar 

  • R. Todeschini V. Consonni (Eds) (2000) Handbook of Molecular Descriptors Wiley-VCH Weinheim, Germany

    Google Scholar 

  • D.M. Hawkins (2004) J. Chem. Inf. Comput. Sci., 44 1

    Google Scholar 

  • S. Wold (1991) Quant. Struct.-Act. Relat., 10 191

    Google Scholar 

  • R.D. Cramer ParticleIII (1993) Perspect. Drug Discov. Design, 1 269

    Google Scholar 

  • D.L. Selwood D.J. Livingstone J.C. Comley A.B. O’Dowd A.T. Hudson P. Jackson K.S. Jandu V.S. Rose J.N. Stables (1990) J. Med. Chem., 33 136

    Google Scholar 

  • D.C. Whitley M.G. Ford D.J. Livingstone (2000) J. Chem. Inf. Comput. Sci., 40 1160

    Google Scholar 

  • D.J. Livingstone E. Rahr (1989) Quant. Struct.-Act. Relat., 8 103

    Google Scholar 

  • O. Kikuch (1987) Quant. Struct.-Act. Relat., 6 179

    Google Scholar 

  • J.M. Sutter S.L. Dixon P.C. Jurs (1995) J. Chem. Inf. Comput. Sci., 35 77

    Google Scholar 

  • B.H. Sumida A.I. Houston J.M. McNamara W.D. Hamilton (1990) J. Theor. Biol., 147 59

    Google Scholar 

  • Rogers, D., In Proceedings of the Fourth International Conference on Genetic Algorithms, San Diego, CA, 1991.

  • R. Leardi R. Boggia M. Terrile (1992) J. Chemometr., 6 267

    Google Scholar 

  • M. Mitchell (Eds) (1999) An Introduction to Genetic Algorithm The MIT Press London, UK

    Google Scholar 

  • B.T. Luke (1994) J. Chem. Inf. Comput. Sci., 34 1279

    Google Scholar 

  • Accelrys, Cerius2, San Diego, CA, 2003.

  • ChemicalComputingGroup, MOE, Quebec, Canada, 2003.

  • Partek, Partek Pro, St. Charles, MO, 2003.

  • P. Chavatte S. Yous C. Marot N. Baurin D. Lesieur (2001) J. Med. Chem., 44 3223

    Google Scholar 

  • A. Cavalli E. Poluzzi F. Ponti ParticleDe M. Recanatini (2002) J. Med. Chem., 45 3844

    Google Scholar 

  • J.H. Holland (Eds) (1975) Adaptation in Natural and Artificial Systems The MIT Press Cambridge, MA

    Google Scholar 

  • H. Kubinyi (1994) Quant. Struct.-Act. Relat., 13 285

    Google Scholar 

  • D. Rogers (1992) Adv. Neural Inform. Process. Syst., 4 1088

    Google Scholar 

  • D. Rogers A.J. Hopfinger (1994) J. Chem. Inf. Comput. Sci., 34 854

    Google Scholar 

  • J.H. Friedman (1991) Ann. Statist., 19 1

    Google Scholar 

  • ChemicalComputingGroup, Svl Exchange Webpage. http://svl.chemcomp.com/, 2003.

  • S. Schefzick C. Kibbey M.P. Bradley (2004) J. Comb. Chem., 6 916

    Google Scholar 

  • Wold, S., In v.d. Waterbeemd H. (Ed.), QSAR: Chemometric Methods in Molecular Design, Verlag-Chemie, Weinheim, Germany, 1994.

  • S.J. Cho M.A. Hermsmeier (2002) J. Chem. Inf. Comput. Sci., 42 927

    Google Scholar 

  • H. Kubinyi (1994) Quant. Struct.-Act. Relat., 13 393

    Google Scholar 

  • C.L. Waller M.P. Bradley (1999) J. Chem. Inf. Comput. Sci., 39 345

    Google Scholar 

  • J.W. McFarland D.J. Gans (1994) Quant. Struct.-Act. Relat., 13 11

    Google Scholar 

  • Todeschini, R., Dragon, Milan, Italy, 2003.

  • Pearlman, R.S., Tripos Inc., St. Louis, MO.

  • The QSAR and Modelling Society. http://www.ndsu.nodak.edu/qsar_soc/, 2003.

  • M. Kendall (Eds) (1955) Rank Correlation Methods Charles Griffin and Co. London, UK

    Google Scholar 

  • M.B. Brown J.K. Benedetti (1977) J. Am. Stat. Assoc., 72 309

    Google Scholar 

  • A. Agresti (Eds) (1990) Categorical Data Analysis John Wiley & Sons, Inc. New York

    Google Scholar 

  • R. Todeschini V. Consonni M. Pavan (2004) Chemometr. Intell. Lab. Syst., 70 55

    Google Scholar 

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Authors and Affiliations

  1. Pfizer Global Research and Development, Discovery Technologies, Ann Arbor Laboratories, 2800 Plymouth Road, Ann Arbor, MI, 48105, USA

    Sabine Schefzick & Mary Bradley

Authors
  1. Sabine Schefzick
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  2. Mary Bradley
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Correspondence to Sabine Schefzick.

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Schefzick, S., Bradley, M. Comparison of commercially available genetic algorithms: GAs as variable selection tool. J Comput Aided Mol Des 18, 511–521 (2004). https://doi.org/10.1007/s10822-004-5322-1

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  • DOI: https://doi.org/10.1007/s10822-004-5322-1

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