Chatchawit Aporntewan

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This paper presents a line of research in genetic algorithms (GAs), called building-block identification. The building blocks (BBs) are common structures inferred from a set of solutions. In simple GA, crossover operator plays an important role in mixing BBs. However, the crossover probably disrupts the BBs because the cut point is chosen at random.(More)
In human cancers, the methylation of long interspersed nuclear element -1 (LINE-1 or L1) retrotransposons is reduced. This occurs within the context of genome wide hypomethylation, and although it is common, its role is poorly understood. L1s are widely distributed both inside and outside of genes, intragenic and intergenic, respectively. Interestingly, the(More)
Our previous work focused on the synthesis of sequential circuits based on a partial input/output sequence. As the behavioural description of the target circuit is not known the correctness of the result can not be verified. This paper proposes a method which increases the correctness percentage of the finite-state machine (FSM) synthesis using multiple(More)
The building blocks are common structures of high-quality solutions. Genetic algorithms often assume the building-block hypothesis. It is hypothesized that the high-quality solutions are composed of building blocks and the solution quality can be improved by composing building blocks. The studies of building blocks are limited to some artificial(More)
We propose a BB identification by simultaneity matrix (BISM) algorithm. The input is a set of-bit solutions denoted by S. The number of solutions is denoted by n = |S|. The output is a partition of bit positions {0,. .. , , − 1}. The BISM is composed of Simultaneity-Matrix-Construction and Fine-Valid-Partition algorithms. Algorithm SMC is outlined as(More)
We propose to use the rough set theory to identify genes affecting rheumatoid arthritis risk from the data collected by the North American Rheumatoid Arthritis Consortium. For each gene, we employ generalized dynamic reducts in the rough set theory to select a subset of single-nucleotide polymorphisms (SNPs) to represent the genetic information from this(More)
The identification of several hundred genomic regions affecting disease risk has proven the ability of genome-wide association studies have proven their ability to identify genetic contributors to disease. Currently, single-nucleotide polymorphism (SNP) association analysis is the most widely used method of genome-wide association data, but recent research(More)
The simultaneity matrix is an × matrix of numbers. It is constructed according to a set of-bit solutions. The matrix element mij is the degree of linkage between bit positions i and j. To exploit the matrix, we partition {0,. .. , , − 1} by putting i and j in the same partition subset if mij is significantly high. The partition represents the bit positions(More)
The interaction among multiple genes and environmental factors can affect an individual's susceptibility to disease. Some genes may not show strong marginal associations when they affect disease risk through interactions with other genes. As a result, these genes may not be identified by single-marker methods that are widely used in genome-wide association(More)