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Retention Index System Transformation Method Incorporated Optimal Molecular Descriptors through Particle Swarm Optimization

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7390))

Abstract

In Comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC/TOF-MS), two dimensional retention index(RI) can be used to aid identification for decrease false-positive rate. However, the amount of collected RI data in some column is obviously less than some popular column. Quantitative structure-retention relationship (QSRR) model is a effective method to eastimate the RI value, but the accuracy still need to improve. A RI transoformation method based on optimal mocular descriptors throught particle swarm optimization is proposed in this paper, 107 molecules with two column experimental RI (DB-17,DB-5) was used to create a dataset. The predictive performance of two methods (PSO-MLR, PSO-Transformation model) was investigated. Ten in-silicon experiments were conducted on each method. Contrasing tranditional QSRR model (PSO-MLR), the proposed method achieved more accuracy predictive results.

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© 2012 Springer-Verlag Berlin Heidelberg

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Zhang, J., Gao, Q., Zheng, C. (2012). Retention Index System Transformation Method Incorporated Optimal Molecular Descriptors through Particle Swarm Optimization. In: Huang, DS., Ma, J., Jo, KH., Gromiha, M.M. (eds) Intelligent Computing Theories and Applications. ICIC 2012. Lecture Notes in Computer Science(), vol 7390. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31576-3_47

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  • DOI: https://doi.org/10.1007/978-3-642-31576-3_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31575-6

  • Online ISBN: 978-3-642-31576-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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