MINE: Module Identification in Networks

<p>Abstract</p> <p>Background</p> <p>Graphical models of network associations are useful for both visualizing and integrating multiple types of association data. Identifying modules, or groups of functionally related gene products, is an important challenge in analyzing biological networks. However, existing tools to identify modules are insufficient when applied to dense networks of experimentally derived interaction data. To address this problem, we have developed an agglomerative clustering method that is able to identify highly modular sets of gene products within highly interconnected molecular interaction networks.</p> <p>Results</p> <p>MINE outperforms MCODE, CFinder, NEMO, SPICi, and MCL in identifying non-exclusive, high modularity clusters when applied to the <it>C. elegans </it>protein-protein interaction network. The algorithm generally achieves superior geometric accuracy and modularity for annotated functional categories. In comparison with the most closely related algorithm, MCODE, the top clusters identified by MINE are consistently of higher density and MINE is less likely to designate overlapping modules as a single unit. MINE offers a high level of granularity with a small number of adjustable parameters, enabling users to fine-tune cluster results for input networks with differing topological properties.</p> <p>Conclusions</p> <p>MINE was created in response to the challenge of discovering high quality modules of gene products within highly interconnected biological networks. The algorithm allows a high degree of flexibility and user-customisation of results with few adjustable parameters. MINE outperforms several popular clustering algorithms in identifying modules with high modularity and obtains good overall recall and precision of functional annotations in protein-protein interaction networks from both <it>S. cerevisiae </it>and <it>C. elegans</it>.</p

Improving community ambulation after stroke: the AMBULATE trial

<p>Abstract</p> <p>Background</p> <p>It has been reported that following rehabilitation, only 7% of stroke survivors are able to walk at a level commensurate with community participation. Previous research indicates that treadmill and overground walking training can improve walking capacity in people living in the community after stroke. The main objectives of the AMBULATE trial are to determine (i) whether a 4-month treadmill walking program is more effective than a 2-month program, compared to control, in improving walking capacity, health and community participation and (ii) the "threshold" walking speed that results in sufficient walking capacity that makes walking self-sustaining.</p> <p>Methods/Design</p> <p>A prospective randomised controlled trial of unsupported treadmill training with a 12 month follow-up with concealed allocation and blinded assessment will be conducted. 210 community-dwelling people after stroke who are able to walk independently but slowly will be recruited and randomly allocated to either a 4 month training group, 2 month training group or the control (no intervention) group. Intervention for the two training groups will occur 3 days per week for 30 minutes each session. Measurements of walking, health and community participation will be taken at baseline, 2 months, 4 months, 6 months and 12 months. This study has obtained ethical approval from the relevant Human Research Ethics Committees.</p> <p>Discussion</p> <p>By improving stroke survivors' walking ability, it is likely also to improve their general wellbeing by promoting better health and greater community participation. Furthermore, if stroke survivors can reach a point where their walking and community participation is self-sustaining, this will reduce the burden of care on family and friends as well as the economic burden on the health system. Given the major demographic shift in developed nations involving significant growth in the aged population, this research will make an important evidence-based contribution to the promotion of healthy ageing.</p> <p>Trial registration</p> <p>This trial is registered with the Australian New Zealand Clinical Trials Registry, (ACTRN012607000227493)</p

Detection of regulator genes and eQTLs in gene networks

Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in non-coding genomic regions. These genetic variants are often also associated to differences in expression levels of nearby genes (they are "expression quantitative trait loci" or eQTLs for short) and presumably play a gene regulatory role, affecting the status of molecular networks of interacting genes, proteins and metabolites. Computational systems biology approaches to reconstruct causal gene networks from large-scale omics data have therefore become essential to understand the structure of networks controlled by eQTLs together with other regulatory genes, and to generate detailed hypotheses about the molecular mechanisms that lead from genotype to phenotype. Here we review the main analytical methods and softwares to identify eQTLs and their associated genes, to reconstruct co-expression networks and modules, to reconstruct causal Bayesian gene and module networks, and to validate predicted networks in silico.Comment: minor revision with typos corrected; review article; 24 pages, 2 figure

Timing Cellular Decision Making Under Noise via Cell–Cell Communication

Many cellular processes require decision making mechanisms, which must act reliably even in the unavoidable presence of substantial amounts of noise. However, the multistable genetic switches that underlie most decision-making processes are dominated by fluctuations that can induce random jumps between alternative cellular states. Here we show, via theoretical modeling of a population of noise-driven bistable genetic switches, that reliable timing of decision-making processes can be accomplished for large enough population sizes, as long as cells are globally coupled by chemical means. In the light of these results, we conjecture that cell proliferation, in the presence of cell–cell communication, could provide a mechanism for reliable decision making in the presence of noise, by triggering cellular transitions only when the whole cell population reaches a certain size. In other words, the summation performed by the cell population would average out the noise and reduce its detrimental impact

The effects of exercise and weight loss in overweight patients with hip osteoarthritis: design of a prospective cohort study

BACKGROUND: Hip osteoarthritis (OA) is recognised as a substantial source of disability, with pain and loss of function as principal symptoms. An aging society and a growing number of overweight people, which is considered a risk factor for OA, contribute to the growing number of cases of hip OA. In knee OA patients, exercise as a single treatment is proven to be very effective towards counteracting pain and physical functionality, but the combination of weight loss and exercise is demonstrated to be even more effective. Exercise as a treatment for hip OA patients is also effective, however evidence is lacking for the combination of weight loss and exercise. Consequently, the aim of this study is to get a first impression of the potential effectiveness of exercise and weight loss in overweight patients suffering from hip OA. METHODS/DESIGN: This is a prospective cohort study. Patients aged 25 or older, overweight (BMI > 25) or obese (BMI > 30), with clinical and radiographic evidence of OA of the hip and able to attend exercise sessions will be included. The intervention is an 8-month exercise and weight-loss lifestyle program. Main goal is to increase aerobic capacity, lose weight and stimulate a low-calorie and active lifestyle. Primary outcome is self-reported physical functioning. Secondary outcomes include pain, stiffness, health-related quality of life and habitual activity level. Weight loss in kilograms and percentage of fat-free mass will also be measured. DISCUSSION: The results of this study will give a first impression of potential effectiveness of exercise and weight loss as a combination program for patients with OA of the hip. Once this program is proven to be effective it may lead to postponing the moment of total hip replacement. TRIAL REGISTRATION NUMBER: NTR1053

Single-Nucleotide Polymorphism Genotyping Identifies a Locally Endemic Clone of Methicillin-Resistant Staphylococcus aureus

We developed, tested, and applied a TaqMan real-time PCR assay for interrogation of three single-nucleotide polymorphisms that differentiate a clade (termed ‘t003-X’) within the radiation of methicillin-resistant Staphylococcus aureus (MRSA) ST225. The TaqMan assay achieved 98% typeability and results were fully concordant with DNA sequencing. By applying this assay to 305 ST225 isolates from an international collection, we demonstrate that clade t003-X is endemic in a single acute-care hospital in Germany at least since 2006, where it has caused a substantial proportion of infections. The strain was also detected in another hospital located 16 kilometers away. Strikingly, however, clade t003-X was not found in 62 other hospitals throughout Germany nor among isolates from other countries, and, hence, displayed a very restricted geographical distribution. Consequently, our results show that SNP-typing may be useful to identify and track MRSA clones that are specific to individual healthcare institutions. In contrast, the spatial dissemination pattern observed here had not been resolved by other typing procedures, including multilocus sequence typing (MLST), spa typing, DNA macrorestriction, and multilocus variable-number tandem repeat analysis (MLVA)

Mortality in Western Australian seniors with chronic respiratory diseases: a cohort study

<p>Abstract</p> <p>Background</p> <p>Relatively few studies have examined survival by pharmacotherapy level and the effects of patient characteristics on mortality by pharmacotherapy level in older chronic respiratory disease (CRD) patients. This study aimed to investigate these issues in older (≥ 65) CRD patients in Western Australia.</p> <p>Methods</p> <p>We identified 108,312 patients ≥ 65 years with CRD during 1992-2006 using linked medical, pharmaceutical, hospital and mortality databases held by the Commonwealth and State governments. Pharmacotherapy classification levels were designed by a clinical consensus panel. Cox regression was used to investigate the study aim.</p> <p>Results</p> <p>Patients using only short acting bronchodilators experienced similar, but slightly worse survival than patients in the highest pharmacotherapy level group using high dose inhaled corticosteroids (ICS) ± long acting bronchodilators (LABs) ± oral steroids. Patients using low to medium dose ICS ± LABs experienced relatively better survival. Also, male gender was associated with all-cause mortality in all patients (HR = 1.72, 95% CI 1.65-1.80) and especially in those in the highest pharmacotherapy level group (HR = 1.97, 95%CI = 1.84-2.10). The P-value of interaction between gender and pharmacotherapy level for the effect on all-cause death was significant (0.0003).</p> <p>Conclusions</p> <p>Older patients with CRD not using ICS experienced the worst survival in this study and may benefit from an escalation in therapeutic regime. Males had a higher risk of death than females, which was more pronounced in the highest pharmacotherapy level group. Hence, primary health care should more actively direct disease management to mild-to-moderate disease patients.</p

Firm-specific, country-specific and region-specific competitive advantages: the case of emerging economy MNEs - Thailand

Increasing levels of regional economic integration have created a new source of international competitiveness for MNEs from an emerging economy, Thailand, in the context of ASEAN economic integration. Building on the theoretical framework of firm-specific advantages (FSAs) and country-specific advantages (CSAs) grounded in internalization theory, we introduce region-specific advantages (RSAs) and advance a novel regional dual-double-diamond model to analyse regional competitiveness. Using both primary and secondary data we find that most Thai firms derive their international competitiveness from CSAs rather than FSAs, and will benefit from ASEAN RSAs. Our study significantly advances the literature on international competitiveness of emerging-economy MNEs

clusterMaker: a multi-algorithm clustering plugin for Cytoscape

<p>Abstract</p> <p>Background</p> <p>In the post-genomic era, the rapid increase in high-throughput data calls for computational tools capable of integrating data of diverse types and facilitating recognition of biologically meaningful patterns within them. For example, protein-protein interaction data sets have been clustered to identify stable complexes, but scientists lack easily accessible tools to facilitate combined analyses of multiple data sets from different types of experiments. Here we present <it>clusterMaker</it>, a Cytoscape plugin that implements several clustering algorithms and provides network, dendrogram, and heat map views of the results. The Cytoscape network is linked to all of the other views, so that a selection in one is immediately reflected in the others. <it>clusterMaker </it>is the first Cytoscape plugin to implement such a wide variety of clustering algorithms and visualizations, including the only implementations of hierarchical clustering, dendrogram plus heat map visualization (tree view), k-means, k-medoid, SCPS, AutoSOME, and native (Java) MCL.</p> <p>Results</p> <p>Results are presented in the form of three scenarios of use: analysis of protein expression data using a recently published mouse interactome and a mouse microarray data set of nearly one hundred diverse cell/tissue types; the identification of protein complexes in the yeast <it>Saccharomyces cerevisiae</it>; and the cluster analysis of the vicinal oxygen chelate (VOC) enzyme superfamily. For scenario one, we explore functionally enriched mouse interactomes specific to particular cellular phenotypes and apply fuzzy clustering. For scenario two, we explore the prefoldin complex in detail using both physical and genetic interaction clusters. For scenario three, we explore the possible annotation of a protein as a methylmalonyl-CoA epimerase within the VOC superfamily. Cytoscape session files for all three scenarios are provided in the Additional Files section.</p> <p>Conclusions</p> <p>The Cytoscape plugin <it>clusterMaker </it>provides a number of clustering algorithms and visualizations that can be used independently or in combination for analysis and visualization of biological data sets, and for confirming or generating hypotheses about biological function. Several of these visualizations and algorithms are only available to Cytoscape users through the <it>clusterMaker </it>plugin. <it>clusterMaker </it>is available via the Cytoscape plugin manager.</p

ExprTarget: An Integrative Approach to Predicting Human MicroRNA Targets

Variation in gene expression has been observed in natural populations and associated with complex traits or phenotypes such as disease susceptibility and drug response. Gene expression itself is controlled by various genetic and non-genetic factors. The binding of a class of small RNA molecules, microRNAs (miRNAs), to mRNA transcript targets has recently been demonstrated to be an important mechanism of gene regulation. Because individual miRNAs may regulate the expression of multiple gene targets, a comprehensive and reliable catalogue of miRNA-regulated targets is critical to understanding gene regulatory networks. Though experimental approaches have been used to identify many miRNA targets, due to cost and efficiency, current miRNA target identification still relies largely on computational algorithms that aim to take advantage of different biochemical/thermodynamic properties of the sequences of miRNAs and their gene targets. A novel approach, ExprTarget, therefore, is proposed here to integrate some of the most frequently invoked methods (miRanda, PicTar, TargetScan) as well as the genome-wide HapMap miRNA and mRNA expression datasets generated in our laboratory. To our knowledge, this dataset constitutes the first miRNA expression profiling in the HapMap lymphoblastoid cell lines. We conducted diagnostic tests of the existing computational solutions using the experimentally supported targets in TarBase as gold standard. To gain insight into the biases that arise from such an analysis, we investigated the effect of the choice of gold standard on the evaluation of the various computational tools. We analyzed the performance of ExprTarget using both ROC curve analysis and cross-validation. We show that ExprTarget greatly improves miRNA target prediction relative to the individual prediction algorithms in terms of sensitivity and specificity. We also developed an online database, ExprTargetDB, of human miRNA targets predicted by our approach that integrates gene expression profiling into a broader framework involving important features of miRNA target site predictions