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This article deals with the identification of gene regulatory networks from experimental data using a statistical machine learning approach. A stochastic model of gene interactions capable of handling missing variables is proposed. It can be described as a dynamic Bayesian network particularly well suited to tackle the stochastic nature of gene regulation(More)
BACKGROUND Transcriptome analysis was applied to characterize the physiological activities of Pseudomonas aeruginosa grown for three days in drip-flow biofilm reactors. Conventional applications of transcriptional profiling often compare two paired data sets that differ in a single experimentally controlled variable. In contrast this study obtained the(More)
BACKGROUND Cellular functions are regulated by complex webs of interactions that might be schematically represented as networks. Two major examples are transcriptional regulatory networks, describing the interactions among transcription factors and their targets, and protein-protein interaction networks. Some patterns, dubbed motifs, have been found to be(More)
Aspergillus fumigatus is a mold responsible for the majority of cases of aspergillosis in humans. To survive in the human body, A. fumigatus must adapt to microenvironments that are often characterized by low nutrient and oxygen availability. Recent research suggests that the ability of A. fumigatus and other pathogenic fungi to adapt to hypoxia contributes(More)
MOTIVATION Although metabolic reactions are unquestionably shaped by evolutionary processes, the degree to which the overall structure and complexity of their interconnections are linked to the phylogeny of species has not been evaluated in depth. Here, we apply an original metabolome representation, termed Network of Interacting Pathways or NIP, with a(More)
BACKGROUND Comparison of metabolic networks across species is a key to understanding how evolutionary pressures shape these networks. By selecting taxa representative of different lineages or lifestyles and using a comprehensive set of descriptors of the structure and complexity of their metabolic networks, one can highlight both qualitative and(More)
The Aspergillus fumigatus sterol regulatory element binding protein (SREBP) SrbA belongs to the basic Helix-Loop-Helix (bHLH) family of transcription factors and is crucial for antifungal drug resistance and virulence. The latter phenotype is especially striking, as loss of SrbA results in complete loss of virulence in murine models of invasive pulmonary(More)
Until recently, the apicomplexan parasites, Cryptosporidium hominis and C. parvum, were considered the same species. However, the two parasites, now considered distinct species, exhibit significant differences in host range, infectivity, and pathogenicity, and their sequenced genomes exhibit only 95-97% identity. The availability of the complete genome(More)
Microarray technology allows for high throughput gene expression studies. However, because of the large amounts of data produced, additional work is required to put the data into biological context. An emerging approach to provide such context is pathway and network analysis. The objective of this work was to design and implement such pathway analysis(More)
Identifying biomarkers that are indicative of a phenotypic state is difficult because of the amount of natural variability which exists in any population. While there are many different algorithms to select biomarkers, previous investigation shows the sensitivity and flexibility of support vector machines (SVM) make them an attractive candidate. Here we(More)