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Identifying candidate disease genes is important to improve medical care. However, this task is challenging in the post-genomic era. Several computational approaches have been proposed to prioritize potential candidate genes relying on protein-protein interaction (PPI) networks. However, the experimental PPI network is usually liable to contain a number of(More)
Microarray experiments can generate data sets with multiple missing expression values, normally due to various experimental problems. Unfortunately, many algorithms for gene expression analysis require a complete matrix of gene array values as input. Effective missing value estimation methods are needed, therefore, to minimize the effect of incomplete data(More)
The identification of protein complexes in protein-protein interaction (PPI) networks has greatly advanced our understanding of biological organisms. Existing computational methods to detect protein complexes are usually based on specific network topological properties of PPI networks. However, due to the inherent complexity of the network structures, the(More)
MOTIVATION Interplays between transcription factors (TFs) and microRNAs (miRNAs) in gene regulation are implicated in various physiological processes. It is thus important to identify biologically meaningful network motifs involving both types of regulators to understand the key co-regulatory mechanisms underlying the cellular identity and function.(More)
MOTIVATION Identification of microRNA regulatory modules (MiRMs) will aid deciphering aberrant transcriptional regulatory network in cancer but is computationally challenging. Existing methods are stochastic or require a fixed number of regulatory modules. RESULTS We propose Mirsynergy, an efficient deterministic overlapping clustering algorithm adapted(More)
Mining sequential rules are an important problem in data mining research. It is commonly used for market decisions, management and behaviour analysis. In traditional association-rule mining, rule interestingness measures such as confidence are used for determining relevant knowledge. They can reduce the size of the search space and select useful or(More)