Biomedical subjects

David R Gilbert

Publications and source records attributed to David R Gilbert.

5 recordsLinked to original sources

PubMed2006

Nicotinamide reduces acute cortical neuronal death and edema in the traumatically injured brain.

Previous studies have shown that administration of nicotinamide (Vitamin B(3)) in animal models of traumatic brain injury (TBI) and ischemia significantly reduced the size of infarction or injury and improved functional recovery. The present study evaluated the ability of nicotinamide to provide acute neuroprotection and edema reduction following TBI. Groups of rats were assigned to nicotinamide (500mg/kg) or saline (1.0ml/kg) treatment conditions and received contusion injuries or sham surgeries. Drug treatment was administered 15min following injury. Brains were harvested 24h later and either processed for histology or water content. Frozen sections were stained with the degenerating neuron stain (Fluoro-Jade B) (FJ) and cell counts were performed at the site of injury. Additional brains were processed for water content (a measure of injury-induced edema). Results of this study showed that administration of nicotinamide following TBI significantly reduced the number of FJ(+) neurons in the injured cortex compared to saline-treated animals. Examination of the water content of the brains also revealed that administration of nicotinamide significantly attenuated the amount of water compared to saline-treated animals in the injured cortex. These results indicate that nicotinamide administration significantly reduced neuronal death and attenuated cerebral edema following injury. The current findings suggest that nicotinamide significantly modulates acute pathophysiological processes following injury and that this may account for its beneficial effects on recovery of function following injury.

Animals↗

PubMed2006

A lock-and-key model for protein-protein interactions.

MOTIVATION: Protein-protein interaction networks are one of the major post-genomic data sources available to molecular biologists. They provide a comprehensive view of the global interaction structure of an organism's proteome, as well as detailed information on specific interactions. Here we suggest a physical model of protein interactions that can be used to extract additional information at an intermediate level: It enables us to identify proteins which share biological interaction motifs, and also to identify potentially missing or spurious interactions. RESULTS: Our new graph model explains observed interactions between proteins by an underlying interaction of complementary binding domains (lock-and-key model). This leads to a novel graph-theoretical algorithm to identify bipartite subgraphs within protein-protein interaction networks where the underlying data are taken from yeast two-hybrid experimental results. By testing on synthetic data, we demonstrate that under certain modelling assumptions, the algorithm will return correct domain information about each protein in the network. Tests on data from various model organisms show that the local and global patterns predicted by the model are indeed found in experimental data. Using functional and protein structure annotations, we show that bipartite subnetworks can be identified that correspond to biologically relevant interaction motifs. Some of these are novel and we discuss an example involving SH3 domains from the Saccharomyces cerevisiae interactome. AVAILABILITY: The algorithm (in Matlab format) is available (see http://www.maths.strath.ac.uk/~aas96106/lock_key.html).

Algorithms↗

PubMed2005

Computational modelling of the receptor-tyrosine-kinase-activated MAPK pathway.

The MAPK (mitogen-activated protein kinase) pathway is one of the most important and intensively studied signalling pathways. It is at the heart of a molecular-signalling network that governs the growth, proliferation, differentiation and survival of many, if not all, cell types. It is de-regulated in various diseases, ranging from cancer to immunological, inflammatory and degenerative syndromes, and thus represents an important drug target. Over recent years, the computational or mathematical modelling of biological systems has become increasingly valuable, and there is now a wide variety of mathematical models of the MAPK pathway which have led to some novel insights and predictions as to how this system functions. In the present review we give an overview of the processes involved in modelling a biological system using the popular approach of ordinary differential equations. Focusing on the MAPK pathway, we introduce the features and functions of the pathway itself before comparing the available models and describing what new biological insights they have led to.

Animals↗

PubMed2005

GeneRank: using search engine technology for the analysis of microarray experiments.

BACKGROUND: Interpretation of simple microarray experiments is usually based on the fold-change of gene expression between a reference and a "treated" sample where the treatment can be of many types from drug exposure to genetic variation. Interpretation of the results usually combines lists of differentially expressed genes with previous knowledge about their biological function. Here we evaluate a method--based on the PageRank algorithm employed by the popular search engine Google--that tries to automate some of this procedure to generate prioritized gene lists by exploiting biological background information. RESULTS: GeneRank is an intuitive modification of PageRank that maintains many of its mathematical properties. It combines gene expression information with a network structure derived from gene annotations (gene ontologies) or expression profile correlations. Using both simulated and real data we find that the algorithm offers an improved ranking of genes compared to pure expression change rankings. CONCLUSION: Our modification of the PageRank algorithm provides an alternative method of evaluating microarray experimental results which combines prior knowledge about the underlying network. GeneRank offers an improvement compared to assessing the importance of a gene based on its experimentally observed fold-change alone and may be used as a basis for further analytical developments.

Algorithms↗

PubMed2004

TOPS: an enhanced database of protein structural topology.

The TOPS database holds topological descriptions of protein structures. These compact and highly abstract descriptions reduce the protein fold to a sequence of Secondary Structure Elements (SSEs) and three sets of pairwise relationships between them, hydrogen bonds relating parallel and anti- parallel beta strands, spatial adjacencies relating neighbouring SSEs, and the chiralities of selected supersecondary structures, including connections in betaalphabeta units and between parallel alpha helices. The database is used as a resource for visualizing folding topologies, fast topological pattern searching and structure comparison. Here, significant enhancements to the TOPS database are described. The topological description has been enhanced to include packing relationships between helices, which significantly improves the description of protein folds with little beta strand content. Further, the topological description has been annotated with sequence information. The query interfaces to the database have been improved and the new version can be found at http://www.tops.leeds.ac.uk/.

Animals↗