Biomedical subjects

Pedro Mendes

Publications and source records attributed to Pedro Mendes.

6 recordsLinked to original sources

PubMed2003

Plant metabolomics: large-scale phytochemistry in the functional genomics era.

Metabolomics or the large-scale phytochemical analysis of plants is reviewed in relation to functional genomics and systems biology. A historical account of the introduction and evolution of metabolite profiling into today's modern comprehensive metabolomics approach is provided. Many of the technologies used in metabolomics, including optical spectroscopy, nuclear magnetic resonance, and mass spectrometry are surveyed. The critical role of bioinformatics and various methods of data visualization are summarized and the future role of metabolomics in plant science assessed.

Computational Biology↗

PubMed2002

Gene networks: how to put the function in genomics.

An increasingly popular model of regulation is to represent networks of genes as if they directly affect each other. Although such gene networks are phenomenological because they do not explicitly represent the proteins and metabolites that mediate cell interactions, they are a logical way of describing phenomena observed with transcription profiling, such as those that occur with popular microarray technology. The ability to create gene networks from experimental data and use them to reason about their dynamics and design principles will increase our understanding of cellular function. We propose that gene networks are also a good way to describe function unequivocally, and that they could be used for genome functional annotation. Here, we review some of the concepts and methods associated with gene networks, with emphasis on their construction based on experimental data.

Animals↗

PubMed2002

Linking the genes: inferring quantitative gene networks from microarray data.

Modern microarray technology is capable of providing data about the expression of thousands of genes, and even of whole genomes. An important question is how this technology can be used most effectively to unravel the workings of cellular machinery. Here, we propose a method to infer genetic networks on the basis of data from appropriately designed microarray experiments. In addition to identifying the genes that affect a specific other gene directly, this method also estimates the strength of such effects. We will discuss both the experimental setup and the theoretical background.

Animals↗

PubMed2002

Quantifying gene networks with regulatory strengths.

A gene network is the collection of regulatory relationships between all genes in a genome. Gene networks are high-level descriptions of cellular biochemistry and show the phenomenological interactions between gene activities. These interactions are mediated by proteins and metabolites. In the gene network approach, only the transcriptome is considered and all biochemistry underlying gene-gene interactions is only implicitly present. In a previous work, we presented a method for inferring gene networks from experimental data, quantifying gene-gene interactions with regulatory strengths. Here, we show how to express these regulatory strengths in terms of properties of the whole biochemical network.

Gene Expression Profiling↗

PubMed2002

Metabolic control in integrated biochemical systems.

Traditional analyses of the control and regulation of steady-state concentrations and fluxes assume the activities of the enzymes to be constant. In living cells, a hierarchical control structure connects metabolic pathways to signal-transduction and gene-expression. Consequently, enzyme activities are not generally constant. This would seem to compromise analyses of control and regulation at the metabolic level. Here, we investigate the concept of metabolic quasi-steady state kinetics as a means of applying metabolic control analysis to hierarchical biochemical systems. We discuss four methods that enable the experimental determination of metabolic control coefficients, and demonstrate these by computer simulations. The best method requires extra measurement of enzyme activities, two others are simpler but are less accurate and one method is bound only to work under special conditions. Our results may assist in evaluating the relative importance of transcriptomics and metabolomics for functional genomics.

Enzymes↗

PubMed2002

Emerging bioinformatics for the metabolome.

Metabolic profiling applied to functional genomics (metabolomics) is in an early stage of development. Here, the technologies used for metabolite profiling are briefly covered, illustrated by a few pioneering studies. Issues related to bioinformatics, namely data analysis, visualisation and archival, are the main focus of this review. Arguably there is already a need for databases containing metabolite profiles specific for a single organism, and a generic repository containing all metabolite profiling results, regardless of species. Data analyses and visualisations that combine the biological context with chemistry details are suggested as being the most promising.

Animals↗