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Current clinical strategy for staging and prognostication of colorectal cancer (CRC) relies mainly upon the TNM or Duke system. This clinicopathological stage is a crude prognostic guide because it reflects in part the delay in diagnosis in the case of an advanced cancer and gives little insight into the biological characteristics of the tumor. We(More)
SUMMARY Pathway-level analysis is a powerful approach enabling interpretation of post-genomic data at a higher level than that of individual biomolecules. Yet, it is currently hard to integrate more than one type of omics data in such an approach. Here, we present a web tool 'IMPaLA' for the joint pathway analysis of transcriptomics or proteomics and(More)
When studying time courses of biological measurements and comparing these to other measurements eg. gene expression and phenotypic endpoints, the analysis is complicated by the fact that although the associated elements may show the same patterns of behaviour, the changes do not occur simultaneously. In these cases standard correlation-based measures of(More)
Many studies now produce parallel data sets from different omics technologies; however, the task of interpreting the acquired data in an integrated fashion is not trivial. This review covers those methods that have been used over the past decade to statistically integrate and interpret metabolomics and transcriptomic data sets. It defines four categories of(More)
Using transcriptomic and metabolomic measurements from the NCI60 cell line panel, together with a novel approach to integration of molecular profile data, we show that the biochemical pathways associated with tumour cell chemosensitivity to platinum-based drugs are highly coincident, i.e. they describe a consensus phenotype. Direct integration of metabolome(More)
The formation, maintenance, and repair of epithelial barriers are of critical importance for whole-body homeostasis. However, the molecular events involved in epithelial tissue maturation are not fully established. To this end, we investigated the molecular processes involved in renal epithelial proximal-tubule monolayer maturation utilizing transcriptomic,(More)
Toxicity testing is vital to protect human health from exposure to toxic chemicals in the environment. Furthermore, combining novel cellular models with molecular profiling technologies, such as metabolomics can add new insight into the molecular basis of toxicity and provide a rich source of biomarkers that are urgently required in a 21st Century approach(More)
MOTIVATION Comparing time courses of gene expression with time courses of phenotypic data may provide new insights in cellular mechanisms. In this study, we compared the performance of five pattern recognition methods with respect to their ability to relate genes and phenotypic data: one classical method (k-means) and four methods especially developed for(More)
Imbalance between high reactive oxygen species formation and antioxidant capacity in the colon and liver has been linked to increased cancer risk. However, knowledge about possible cell line-specific oxidative stress-mechanisms is limited. To explore this further, gene expression data from a human liver and colon cell line (HepG2/Caco-2), both exposed to(More)
MOTIVATION Metabolic profiles derived from high resolution (1)H-NMR data are complex, therefore statistical and machine learning approaches are vital for extracting useful information and biological insights. Focused modelling on targeted subsets of metabolites and samples can improve the predictive ability of models, and techniques such as genetic(More)