Huai-Kuang Tsai

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This work proposes an evolutionary algorithm, called the heterogeneous selection evolutionary algorithm (HeSEA), for solving large traveling salesman problems (TSP). The strengths and limitations of numerous well-known genetic operators are first analyzed, along with local search methods for TSPs from their solution qualities and mechanisms for preserving(More)
Knowing transcription factors (TFs) involved in the yeast cell cycle is helpful for understanding the regulation of yeast cell cycle genes. We therefore developed two methods for predicting (i) individual cell cycle TFs and (ii) synergistic TF pairs. The essential idea is that genes regulated by a cell cycle TF should have higher (lower, if it is a(More)
In this paper the Family Competition Genetic Algorithm (FCGA) is applied to analyze DNAmicroarray data. DNA Microarray technology is a significant impact on genomics study. The proposed approach consists of global and local strategies by integrating the family competition, edge assembly crossover, and neighbor-join mutation. Experiments are performed to(More)
MOTIVATION Disulfide bonds play an important role in protein folding. A precise prediction of disulfide connectivity can strongly reduce the conformational search space and increase the accuracy in protein structure prediction. Conventional disulfide connectivity predictions use sequence information, and prediction accuracy is limited. Here, by using an(More)
This study presents an evolutionary algorithm, called a heterogeneous selection genetic algorithm (HeSGA), for analyzing the patterns of gene expression on microarray data. Microarray technologies have provided the means to monitor the expression levels of a large number of genes simultaneously. Gene clustering and gene ordering are important in analyzing a(More)
MOTIVATION Gene regulation involves complicated mechanisms such as cooperativity between a set of transcription factors (TFs). Previous studies have used target genes shared by two TFs as a clue to infer TF-TF interactions. However, this task remains challenging because the target genes with low binding affinity are frequently omitted by experimental data,(More)
Both cis and trans mutations contribute to gene expression divergence within and between species. We used Saccharomyces cerevisiae as a model organism to estimate the relative contributions of cis and trans variations to the expression divergence between a laboratory (BY) and a wild (RM) strain of yeast. We examined whether genes regulated by a single(More)
We have developed an evolutionary approach to predicting protein side-chain conformations. This approach, referred to as the Gaussian Evolutionary Method (GEM), combines both discrete and continuous global search mechanisms. The former helps speed up convergence by reducing the size of rotamer space, whereas the latter, integrating decreasing-based Gaussian(More)
Divergence of transcription factor binding sites is considered to be an important source of regulatory evolution. The associations between transcription factor binding sites and phenotypic diversity have been investigated in many model organisms. However, the understanding of other factors that contribute to it is still limited. Recent studies have(More)
Transcription factor (TF) binding is determined by the presence of specific sequence motifs (SM) and chromatin accessibility, where the latter is influenced by both chromatin state (CS) and DNA structure (DS) properties. Although SM, CS, and DS have been used to predict TF binding sites, a predictive model that jointly considers CS and DS has not been(More)