ArticleAdvances and applications in bioinformatics and chemistry : AABC2010
Pharmacogenomics of drug efficacy in the interferon treatment of chronic hepatitis C using classification algorithms.
Article in Advances and applications in bioinformatics and chemistry : AABC, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Pattern Recognition Algorithms in Pharmacogenomics and Drug Repurposing-Case Study: Ribavirin and Lopinavir.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Arterial stiffness and biological parameters: A decision tree machine learning application in hypertensive participants.PloS one · 2023Article
- Arterial Stiffness Determinants for Primary Cardiovascular Prevention among Healthy Participants.Journal of clinical medicine · 2022Article
- Risk prediction model of dyslipidaemia over a 5-year period based on the Taiwan MJ health check-up longitudinal database.Lipids in health and disease · 2018Article
- A Comparison between Decision Tree and Random Forest in Determining the Risk Factors Associated with Type 2 Diabetes.Journal of research in health sciences · 2018Article
- Machine learning and systems genomics approaches for multi-omics data.Biomarker research · 2017Review
- Resting heart rate as a marker for identifying the risk of undiagnosed type 2 diabetes mellitus: a cross-sectional survey.BMC public health · 2014Article
- Comparison of classification algorithms with wrapper-based feature selection for predicting osteoporosis outcome based on genetic factors in a taiwanese women population.International journal of endocrinology · 2013Article
- Assessing gene-gene interactions in pharmacogenomics.Molecular diagnosis & therapy · 2012Review
- Article
- Relationship between resting pulse rate and lipid metabolic dysfunctions in Chinese adults living in rural areas.PloS one · 2012Article
- Article
- Pharmacogenomics of chronic hepatitis C therapy with genome-wide association studies.Journal of experimental pharmacology · 2010Review
Corrections and comments
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Authors and funding
3 authors.
Funding
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Abstract
Chronic hepatitis C (CHC) patients often stop pursuing interferon-alfa and ribavirin (IFN-alfa/RBV) treatment because of the high cost and associated adverse effects. It is highly desirable, both clinically and economically, to establish tools to distinguish responders from nonresponders and to predict possible outcomes of the IFN-alfa/RBV treatments. Single nucleotide polymorphisms (SNPs) can be used to understand the relationship between genetic inheritance and IFN-alfa/RBV therapeutic response. The aim in this study was to establish a predictive model based on a pharmacogenomic approach. Our study population comprised Taiwanese patients with CHC who were recruited from multiple sites in Taiwan. The genotyping data was generated in the high-throughput genomics lab of Vita Genomics, Inc. With the wrapper-based feature selection approach, we employed multilayer feedforward neural network (MFNN) and logistic regression as a basis for comparisons. Our data revealed that the MFNN models were superior to the logistic regression model. The MFNN approach provides an efficient way to develop a tool for distinguishing responders from nonresponders prior to treatments. Our preliminary results demonstrated that the MFNN algorithm is effective for deriving models for pharmacogenomics studies and for providing the link from clinical factors such as SNPs to the responsiveness of IFN-alfa/RBV in clinical association studies in pharmacogenomics.
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