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Biomedical subjects

Kung-Hao Liang

Publications and source records attributed to Kung-Hao Liang.

4 recordsLinked to original sources

Pattern-recognition techniques with haplotype analysis in pharmacogenomics.

Single nucleotide polymorphisms (SNPs) can be used in clinical association studies to determine the contribution of genes to drug efficacy. However, it would be extremely inefficient to test all the 10 million common SNPs for an association study. Here we review haplotype analysis and pattern-recognition techniques to systematically select candidate SNPs for candidate-gene association studies in pharmacogenomics. First, we survey linkage disequilibrium methods to identify tag SNPs and explore the use of haplotypes as genetic markers that are correlated and associated with drug efficacy. Secondly, we investigate pattern-recognition algorithms and statistical analyses to assess drug efficacy based on SNPs and other factors. Finally, we study pattern-recognition approaches to evaluate the epistasis among genes and SNPs. These techniques may provide tools for clinical association studies and help find genes/SNPs involved in responses to therapeutic drugs or adverse drug reactions.

Animals↗

An algorithm for model construction and its applications to pharmacogenomic studies.

A model depicts the relationship between clinical phenotypes and genotypes on a set of genetic polymorphisms. After the model is constructed and validated, it may be used to predict clinical phenotypes such as traits of complex diseases. A pharmacogenomic model is used to predict the efficacies or adverse drug reactions of a medication. The construction of a model is a challenging task. This is because a single-locus polymorphism does not contain enough information to stratify patients in general, given the complex biological mechanisms involved. An exhaustive search for the correct combination of genotypes across multiple loci is, however, computationally infeasible. We are, thus, motivated to propose a novel algorithm for the construction of models using the multiple single-nucleotide polymorphism (SNP) information in diplotype forms. This algorithm utilizes the techniques of genetic algorithms and Boolean algebra (GABA). The proposed algorithm is tested on simulated data, as well as real genotype datasets of chronic hepatitis C patients treated with interferon-combined therapy. A model for predicting the treatment efficacy is constructed and validated. The results showed that the proposed algorithm is very effective in deriving models comprising multiple SNPs.

Algorithms↗

Analysis of epistasis for diabetic nephropathy among type 2 diabetic patients.

Diabetic nephropathy (DN) is one of the most serious complications of diabetes, accounting for the majority of patients with end-stage renal disease. The molecular pathogenesis of DN involves multiple pathways in a complex, partially resolved manner. The paper presents an exploratory epistatic study for DN. Association analysis were performed on 231 SNP loci in a cohort of 264 type 2 diabetes patients, followed by the epistasis analysis using the multifactor dimensionality reduction and the genetic algorithm with Boolean algebra. A two-locus epistatic effect of EGFR and RXRG was identified, with a cross-validation consistency of 91.7%.

Aged↗

Adaptive scale fixing for multiscale texture segmentation.

This paper addresses two challenging issues in unsupervised multiscale texture segmentation: determining adequate spatial and feature resolutions for different regions of the image, and utilizing information across different scales/resolutions. The center of a homogeneous texture is analyzed using coarse spatial resolution, and its border is detected using fine spatial resolution so as to locate the boundary accurately. The extraction of texture features is achieved via a multiresolution pyramid. The feature values are integrated across scales/resolutions adaptively. The number of textures is determined automatically using the variance ratio criterion. Experimental results on synthetic and real images demonstrate the improvement in performance of the proposed multiscale scheme over single scale approaches.

Algorithms↗