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MicroRNAs (miRNAs) play an indispensable role in cancer initiation and progression. Different cancers have some common hallmarks in general. Analyzing miRNAs that consistently contribute to different cancers can help us to discover the relationship between miRNAs and traits shared by cancers. Most previous works focus on analyzing single miRNA. However,(More)
To enhance the performance of harmony search (HS) algorithm on solving the discrete optimization problems, this paper proposes a novel harmony search algorithm based on teaching-learning (HSTL) strategies to solve 0-1 knapsack problems. In the HSTL algorithm, firstly, a method is presented to adjust dimension dynamically for selected harmony vector in(More)
MOTIVATION Two-locus model is a typical significant disease model to be identified in genome-wide association study (GWAS). Due to intensive computational burden and diversity of disease models, existing methods have drawbacks on low detection power, high computation cost, and preference for some types of disease models. METHOD In this study, two scoring(More)
The stratification of cancer into subtypes that are significantly associated with clinical outcomes is beneficial for targeted prognosis and treatment. In this study, we integrated somatic mutation and gene expression data to identify clusters of patients. In contrast to previous studies, we constructed cancer-type-specific significant co-expression(More)
Formation and progression of complex diseases are generally the joint effect of genetic and epigenetic disorders, thus an integrative analysis of epigenetic and genetic data is essential for understanding mechanism of the diseases. In this study, we integrate Illuminate 450k DNA methylation and gene expression data to calculate the weights of gene network(More)
Harmony Search (HS) and Teaching-Learning-Based Optimization (TLBO) as new swarm intelligent optimization algorithms have received much attention in recent years. Both of them have shown outstanding performance for solving NP-Hard optimization problems. However, they also suffer dramatic performance degradation for some complex high-dimensional optimization(More)
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