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CLC number: R512.6

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Received: 2008-02-13

Revision Accepted: 2008-04-26

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Journal of Zhejiang University SCIENCE B 2008 Vol.9 No.6 P.474~481

http://doi.org/10.1631/jzus.B0820044


Metabonomic analysis of hepatitis B virus-induced liver failure: identification of potential diagnostic biomarkers by fuzzy support vector machine


Author(s):  Yong MAO, Xin HUANG, Ke YU, Hai-bin QU, Chang-xiao LIU, Yi-yu CHENG

Affiliation(s):  Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):   chengyy@zju.edu.cn

Key Words:  Metabolite profile analysis, Potential diagnostic biomarker identification, k-nearest neighbor (KNN), Fuzzy support vector machine (FSVM), Exhaustive search (ES), Gas chromatography-mass spectrometry (GC-MS), Hepatitis B virus (HBV)-induced liver f


Yong MAO, Xin HUANG, Ke YU, Hai-bin QU, Chang-xiao LIU, Yi-yu CHENG. Metabonomic analysis of hepatitis B virus-induced liver failure: identification of potential diagnostic biomarkers by fuzzy support vector machine[J]. Journal of Zhejiang University Science B, 2008, 9(6): 474~481.

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author="Yong MAO, Xin HUANG, Ke YU, Hai-bin QU, Chang-xiao LIU, Yi-yu CHENG",
journal="Journal of Zhejiang University Science B",
volume="9",
number="6",
pages="474~481",
year="2008",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.B0820044"
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%0 Journal Article
%T Metabonomic analysis of hepatitis B virus-induced liver failure: identification of potential diagnostic biomarkers by fuzzy support vector machine
%A Yong MAO
%A Xin HUANG
%A Ke YU
%A Hai-bin QU
%A Chang-xiao LIU
%A Yi-yu CHENG
%J Journal of Zhejiang University SCIENCE B
%V 9
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%P 474~481
%@ 1673-1581
%D 2008
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.B0820044

TY - JOUR
T1 - Metabonomic analysis of hepatitis B virus-induced liver failure: identification of potential diagnostic biomarkers by fuzzy support vector machine
A1 - Yong MAO
A1 - Xin HUANG
A1 - Ke YU
A1 - Hai-bin QU
A1 - Chang-xiao LIU
A1 - Yi-yu CHENG
J0 - Journal of Zhejiang University Science B
VL - 9
IS - 6
SP - 474
EP - 481
%@ 1673-1581
Y1 - 2008
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.B0820044


Abstract: 
hepatitis B virus (HBV)-induced liver failure is an emergent liver disease leading to high mortality. The severity of liver failure may be reflected by the profile of some metabolites. This study assessed the potential of using metabolites as biomarkers for liver failure by identifying metabolites with good discriminative performance for its phenotype. The serum samples from 24 HBV-induced liver failure patients and 23 healthy volunteers were collected and analyzed by gas chromatography-mass spectrometry (GC-MS) to generate metabolite profiles. The 24 patients were further grouped into two classes according to the severity of liver failure. Twenty-five commensal peaks in all metabolite profiles were extracted, and the relative area values of these peaks were used as features for each sample. Three algorithms, F-test, k-nearest neighbor (KNN) and fuzzy support vector machine (FSVM) combined with exhaustive search (ES), were employed to identify a subset of metabolites (biomarkers) that best predict liver failure. Based on the achieved experimental dataset, 93.62% predictive accuracy by 6 features was selected with FSVM-ES and three key metabolites, glyceric acid, cis-aconitic acid and citric acid, are identified as potential diagnostic biomarkers.

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