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BACKGROUND Gene co-expression networks are often constructed by computing some measure of similarity between expression levels of gene transcripts and subsequently applying a high-pass filter to remove all but the most likely biologically-significant relationships. The selection of this expression threshold necessarily has a significant effect on any(More)
A wealth of clustering algorithms has been applied to gene co-expression experiments. These algorithms cover a broad range of approaches, from conventional techniques such as k-means and hierarchical clustering, to graphical approaches such as k-clique communities, weighted gene co-expression networks (WGCNA) and paraclique. Comparison of these methods to(More)
Genes with common functions often exhibit correlated expression levels, which can be used to identify sets of interacting genes from microarray data. Microarrays typically measure expression across genomic space, creating a massive matrix of co-expression that must be mined to extract only the most relevant gene interactions. We describe a graph theoretical(More)
High throughput biological data need to be processed, analyzed, and interpreted to address problems in life sciences. Bioinformatics, computational biology, and systems biology deal with biological problems using computational methods. Clustering is one of the methods used to gain insight into biological processes, particularly at the genomics level.(More)
Tools of molecular biology and the evolving tools of genomics can now be exploited to study the genetic regulatory mechanisms that control cellular responses to a wide variety of stimuli. These responses are highly complex, and involve many genes and gene products. The main objectives of this paper are to describe a novel research program centered on(More)
The tools of molecular biology and the evolving tools of genomics can now be exploited to study the genetic regulatory mechanisms that control cellular responses to a wide variety of stimuli. These responses are highly complex, and involve many genes and gene products. The main objectives of this paper are to describe a novel research program centered on(More)
Aspergillus flavus is a pathogenic fungus infecting maize and producing aflatoxins that are health hazards to humans and animals. Characterizing host defense mechanism and prioritizing candidate resistance genes are important to the development of resistant maize germplasm. We investigated methods amenable for the analysis of the significance and relations(More)
BACKGROUND The identification of novel genes by high-throughput studies of complex diseases is complicated by the large number of potential genes. However, since disease-associated genes tend to interact, one solution is to arrange them in modules based on co-expression data and known gene interactions. The hypothesis of this study was that such a module(More)
Mapping RNA sequences to a reference genome often results in high percentages of short reads assigned to multiple locations within the genome. These mappings are known as "ambiguous mappings" and are often discarded by sequence mapping tools and pipelines. The number of ambiguous mappings within these data sets can sometimes be significantly large,(More)
– Ensemble clustering is a promising approach that combines the results of multiple clustering algorithms to obtain a consensus partition by merging different partitions based upon well-defined rules. In this study, we use an ensemble clustering approach for merging the results of five different clustering algorithms that are sometimes used in(More)