Prediction of proinflammatory potentials of engine exhausts by integrating chemical and biological features

Chia Chi Wang, Ying Chi Lin, Yuan Chung Lin, Syu Ruei Jhang, Chun Wei Tung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The increasing prevalence of immune-related diseases has raised concerns about immunotoxicity of engine exhausts. The evaluation of immunotoxicity associated with engine exhausts has relied on expensive and timeconsuming experiments. In this study, a computational method named CBM was developed for predicting proinflammatory potentials of engine exhausts using chemical and biological data which are routinely analyzed for toxicity evaluation. The CBM model, based on a principal component regression algorithm, performs well with high correlation coefficient values of 0.972 and 0.849 obtained from training and independent test sets, respectively. In contrast, chemical or biological features alone showed poor correlation with the toxicity. The model indicates the importance of the utilization of both chemical and biological features for developing an effective model. The proposed method could be further developed and applied to predict bioactivities of mixtures.

Original languageEnglish
Title of host publicationBioinformatics and Biomedical Engineering - 4th International Conference, IWBBIO 2016, Proceedings
EditorsFrancisco Ortuno, Ignacio Rojas
PublisherSpringer Verlag
Pages293-303
Number of pages11
ISBN (Print)9783319317434
DOIs
Publication statusPublished - Jan 1 2016
Externally publishedYes
Event4th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2016 - Granada, Spain
Duration: Apr 20 2016Apr 22 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9656
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2016
CountrySpain
CityGranada
Period4/20/164/22/16

Fingerprint

Exhaust systems (engine)
Engine
Toxicity
Prediction
Principal Component Regression
Evaluation
Test Set
Computational methods
Independent Set
Bioactivity
Correlation coefficient
Computational Methods
Model-based
Predict
Model
Experiment
Experiments

Keywords

  • Engine exhaust
  • Genotoxicity
  • Immunotoxicity
  • Principal component regression
  • Proinflammatory potential

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Wang, C. C., Lin, Y. C., Lin, Y. C., Jhang, S. R., & Tung, C. W. (2016). Prediction of proinflammatory potentials of engine exhausts by integrating chemical and biological features. In F. Ortuno, & I. Rojas (Eds.), Bioinformatics and Biomedical Engineering - 4th International Conference, IWBBIO 2016, Proceedings (pp. 293-303). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9656). Springer Verlag. https://doi.org/10.1007/978-3-319-31744-1_26

Prediction of proinflammatory potentials of engine exhausts by integrating chemical and biological features. / Wang, Chia Chi; Lin, Ying Chi; Lin, Yuan Chung; Jhang, Syu Ruei; Tung, Chun Wei.

Bioinformatics and Biomedical Engineering - 4th International Conference, IWBBIO 2016, Proceedings. ed. / Francisco Ortuno; Ignacio Rojas. Springer Verlag, 2016. p. 293-303 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9656).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wang, CC, Lin, YC, Lin, YC, Jhang, SR & Tung, CW 2016, Prediction of proinflammatory potentials of engine exhausts by integrating chemical and biological features. in F Ortuno & I Rojas (eds), Bioinformatics and Biomedical Engineering - 4th International Conference, IWBBIO 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9656, Springer Verlag, pp. 293-303, 4th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2016, Granada, Spain, 4/20/16. https://doi.org/10.1007/978-3-319-31744-1_26
Wang CC, Lin YC, Lin YC, Jhang SR, Tung CW. Prediction of proinflammatory potentials of engine exhausts by integrating chemical and biological features. In Ortuno F, Rojas I, editors, Bioinformatics and Biomedical Engineering - 4th International Conference, IWBBIO 2016, Proceedings. Springer Verlag. 2016. p. 293-303. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-31744-1_26
Wang, Chia Chi ; Lin, Ying Chi ; Lin, Yuan Chung ; Jhang, Syu Ruei ; Tung, Chun Wei. / Prediction of proinflammatory potentials of engine exhausts by integrating chemical and biological features. Bioinformatics and Biomedical Engineering - 4th International Conference, IWBBIO 2016, Proceedings. editor / Francisco Ortuno ; Ignacio Rojas. Springer Verlag, 2016. pp. 293-303 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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