Evaluating Ortholog Prediction Algorithms in a Yeast Model Clade

RSD, respectively, so that they can predict orthologs across multiple taxa) against a set of 2,723 groups of high-quality curated orthologs from 6 Saccharomycete yeasts in the Yeast Gene Order Browser. of all algorithms dramatically increased in these traps.) for evolutionary and functional genomics studies where the objective is the accurate inference of single-copy orthologs (e.g., molecular phylogenetics), but that all algorithms fail to accurately predict orthologs when paralogy is rampant

Proton nuclear magnetic resonance spectroscopic detection of oligomannosidic n glycans in alpha-mannosidosis: a method of monitoring treatment

In Alpha-mannosidosis (MIM 248500) the patients accumulate mainly unbranched oligosaccharide chains in the lysosomes in all body tissues, including the brain. With ensuing therapeutic modalities in man (BMT and ERT) non-invasive methods of monitoring the effect of treatment are needed. Paramount is the possible effect of the treatment on the brain, since this organ is regarded as difficult to reach because of the blood-brain barrier. We therefore performed proton nuclear magnetic resonance spectroscopy (MRS) of the brain in two untreated patients, and a 16-year-old patient treated with BMT at the age of 10 to assess whether this non-invasive method could be applied in the monitoring of the accumulation of abnormal chemicals in the brain of patients. We found an abnormal peak that was not present in the treated patient. A similar pattern was also found in MRS of urine from patients, reflecting the concentration of oligosaccharides in serum and tissues. We therefore conclude that MRS can be a useful method to monitor the effect of treatment for Alpha-Mannosidosis

A Genome-Wide Analysis of Promoter-Mediated Phenotypic Noise in Escherichia coli

Gene expression is subject to random perturbations that lead to fluctuations in the rate of protein production. As a consequence, for any given protein, genetically identical organisms living in a constant environment will contain different amounts of that particular protein, resulting in different phenotypes. This phenomenon is known as “phenotypic noise.” In bacterial systems, previous studies have shown that, for specific genes, both transcriptional and translational processes affect phenotypic noise. Here, we focus on how the promoter regions of genes affect noise and ask whether levels of promoter-mediated noise are correlated with genes' functional attributes, using data for over 60% of all promoters in Escherichia coli. We find that essential genes and genes with a high degree of evolutionary conservation have promoters that confer low levels of noise. We also find that the level of noise cannot be attributed to the evolutionary time that different genes have spent in the genome of E. coli. In contrast to previous results in eukaryotes, we find no association between promoter-mediated noise and gene expression plasticity. These results are consistent with the hypothesis that, in bacteria, natural selection can act to reduce gene expression noise and that some of this noise is controlled through the sequence of the promoter region alon

Bioinformatics on the Cloud Computing Platform Azure

We discuss the applicability of the Microsoft cloud computing platform, Azure, for bioinformatics. We focus on the usability of the resource rather than its performance. We provide an example of how R can be used on Azure to analyse a large amount of microarray expression data deposited at the public database ArrayExpress. We provide a walk through to demonstrate explicitly how Azure can be used to perform these analyses in Appendix S1 and we offer a comparison with a local computation. We note that the use of the Platform as a Service (PaaS) offering of Azure can represent a steep learning curve for bioinformatics developers who will usually have a Linux and scripting language background. On the other hand, the presence of an additional set of libraries makes it easier to deploy software in a parallel (scalable) fashion and explicitly manage such a production run with only a few hundred lines of code, most of which can be incorporated from a template. We propose that this environment is best suited for running stable bioinformatics software by users not involved with its development. © 2014 Shanahan et al

A quantitative approach to study indirect effects among disease proteins in the human protein interaction network

<p>Abstract</p> <p>Background</p> <p>Systems biology makes it possible to study larger and more intricate systems than before, so it is now possible to look at the molecular basis of several diseases in parallel. Analyzing the interaction network of proteins in the cell can be the key to understand how complex processes lead to diseases. Novel tools in network analysis provide the possibility to quantify the key interacting proteins in large networks as well as proteins that connect them. Here we suggest a new method to study the relationships between topology and functionality of the protein-protein interaction network, by identifying key mediator proteins possibly maintaining indirect relationships among proteins causing various diseases.</p> <p>Results</p> <p>Based on the i2d and OMIM databases, we have constructed (i) a network of proteins causing five selected diseases (DP, disease proteins) plus their interacting partners (IP, non-disease proteins), the DPIP network and (ii) a protein network showing only these IPs and their interactions, the IP network. The five investigated diseases were (1) various cancers, (2) heart diseases, (3) obesity, (4) diabetes and (5) autism. We have quantified the number and strength of IP-mediated indirect effects between the five groups of disease proteins and hypothetically identified the most important mediator proteins linking heart disease to obesity or diabetes in the IP network. The results present the relationship between mediator role and centrality, as well as between mediator role and functional properties of these proteins.</p> <p>Conclusions</p> <p>We show that a protein which plays an important indirect mediator role between two diseases is not necessarily a hub in the PPI network. This may suggest that, even if hub proteins and disease proteins are trivially of great interest, mediators may also deserve more attention, especially if disease-disease associations are to be understood. Identifying the hubs may not be sufficient to understand particular pathways. We have found that the mediators between heart diseases and obesity, as well as heart diseases and diabetes are of relatively high functional importance in the cell. The mediator proteins suggested here should be experimentally tested as products of hypothetical disease-related proteins.</p

Age-related delay in information accrual for faces: Evidence from a parametric, single-trial EEG approach

Background: In this study, we quantified age-related changes in the time-course of face processing by means of an innovative single-trial ERP approach. Unlike analyses used in previous studies, our approach does not rely on peak measurements and can provide a more sensitive measure of processing delays. Young and old adults (mean ages 22 and 70 years) performed a non-speeded discrimination task between two faces. The phase spectrum of these faces was manipulated parametrically to create pictures that ranged between pure noise (0% phase information) and the undistorted signal (100% phase information), with five intermediate steps. Results: Behavioural 75% correct thresholds were on average lower, and maximum accuracy was higher, in younger than older observers. ERPs from each subject were entered into a single-trial general linear regression model to identify variations in neural activity statistically associated with changes in image structure. The earliest age-related ERP differences occurred in the time window of the N170. Older observers had a significantly stronger N170 in response to noise, but this age difference decreased with increasing phase information. Overall, manipulating image phase information had a greater effect on ERPs from younger observers, which was quantified using a hierarchical modelling approach. Importantly, visual activity was modulated by the same stimulus parameters in younger and older subjects. The fit of the model, indexed by R2, was computed at multiple post-stimulus time points. The time-course of the R2 function showed a significantly slower processing in older observers starting around 120 ms after stimulus onset. This age-related delay increased over time to reach a maximum around 190 ms, at which latency younger observers had around 50 ms time lead over older observers. Conclusion: Using a component-free ERP analysis that provides a precise timing of the visual system sensitivity to image structure, the current study demonstrates that older observers accumulate face information more slowly than younger subjects. Additionally, the N170 appears to be less face-sensitive in older observers

Genome Majority Vote Improves Gene Predictions

Recent studies have noted extensive inconsistencies in gene start sites among orthologous genes in related microbial genomes. Here we provide the first documented evidence that imposing gene start consistency improves the accuracy of gene start-site prediction. We applied an algorithm using a genome majority vote (GMV) scheme to increase the consistency of gene starts among orthologs. We used a set of validated Escherichia coli genes as a standard to quantify accuracy. Results showed that the GMV algorithm can correct hundreds of gene prediction errors in sets of five or ten genomes while introducing few errors. Using a conservative calculation, we project that GMV would resolve many inconsistencies and errors in publicly available microbial gene maps. Our simple and logical solution provides a notable advance toward accurate gene maps

Algorithm of OMA for large-scale orthology inference

Since the publication of our article (Roth, Gonnet, and Dessimoz: BMC Bioinformatics 2008 9: 518), we have noticed several errors, which we correct in the following

GoLoco motif proteins binding to Gαi1: insights from molecular simulations

Molecular dynamics simulations, computational alanine scanning and sequence analysis were used to investigate the structural properties of the Gαi1/GoLoco peptide complex. Using these methodologies, binding of the GoLoco motif peptide to the Gαi1 subunit was found to restrict the relative movement of the helical and catalytic domains in the Gαi1 subunit, which is in agreement with a proposed mechanism of GDP dissociation inhibition by GoLoco motif proteins. In addition, the results provide further insights into the role of the “Switch IV” region located within the helical domain of Gα, the conformation of which might be important for interactions with various Gα partners

Women and postfertilization effects of birth control: consistency of beliefs, intentions and reported use

BACKGROUND: This study assesses the consistency of responses among women regarding their beliefs about the mechanisms of actions of birth control methods, beliefs about when human life begins, the intention to use or not use birth control methods that they believe may act after fertilization or implantation, and their reported use of specific methods. METHODS: A questionnaire was administered in family practice and obstetrics and gynecology clinics in Salt Lake City, Utah, and Tulsa, Oklahoma. Participants included women ages 18–50 presenting for any reason and women under age 18 presenting for family planning or pregnancy care. Analyses were based on key questions addressing beliefs about whether specific birth control methods may act after fertilization, beliefs about when human life begins, intention to use a method that may act after fertilization, and reported use of specific methods. The questionnaire contained no information about the mechanism of action of any method of birth control. Responses were considered inconsistent if actual use contradicted intentions, if one intention contradicted another, or if intentions contradicted beliefs. RESULTS: Of all respondents, 38% gave consistent responses about intention to not use or to stop use of any birth control method that acted after fertilization, while 4% gave inconsistent responses. The corresponding percentages for birth control methods that work after implantation were 64% consistent and 2% inconsistent. Of all respondents, 34% reported they believed that life begins at fertilization and would not use any birth control method that acts after fertilization (a consistent response), while 3% reported they believed that life begins at fertilization but would use a birth control method that acts after fertilization (inconsistent). For specific methods of birth control, less than 1% of women gave inconsistent responses. A majority of women (68% or greater) responded accurately about the mechanism of action of condoms, abstinence, sterilization, and abortion, but a substantial percentage of women (between 19% and 57%) were uncertain about the mechanisms of action of oral contraceptives, intrauterine devices (IUDs), Depo-Provera, or natural family planning. CONCLUSION: Women who believe that life begins at fertilization may not intend to use a birth control method that could have postfertilization effects. More research is needed to understand the relative importance of postfertilization effects for women in other populations, and in relation to other properties of and priorities for birth control methods. However, many women were uncertain about the mechanisms of action of specific methods. To respect the principles of informed consent, some women may need more education about what is known and not known about the mechanisms of action of birth control methods