RankViaContact: ranking and visualization of amino acid contacts

SUMMARY: RankViaContact is a web service for calculation of residue-residue contact energies in proteins based on a coarse-grained model, and for visualization of interactions. The service provides information about ranked contact energies of residues, coordination numbers and the relative solvent accessibility of selected residues, as well as sequence and structure information. The program can be used to design stabilizing mutations, to analyze residue-residue contacts and to study the consequences of mutations. AVAILABILITY: http://bioinf.uta.fi/Rank.htm.     

RANKVET: A new ranking method for comparing and prioritizing the environmental risk of veterinary pharmaceuticals

In recent years veterinary medicinal products (VMPs) have been recognized as emerging contaminants, giving rise to concerns regarding their environmental impact. Due to the high number of utilized VMPs, it is necessary to develop tools (indicators) for ranking these compounds according to their environmental risk relevance. These indicators can be useful, for example, for setting up monitoring programmes, and more in general for risk management purposes. In this paper we propose a new scoring system method (RANKVET) that enables ranking the risk of VMPs for aquatic and terrestrial organisms. The procedure is fully based on the information required by the EU Directives and Regulations for marketing authorization of VMPs and Veterinary International Conference on Harmonization (VICH) guidelines. According to the latter, if the environmental risk assessment of a VMP indicates an unacceptable risk to the environment, i.e., the risk quotient (RQ) consisting of the ratio of Predicted Environmental Concentration (PEC) to Predicted No Effect Concentration (PNEC) is ≥1, then mitigation measures should be proposed by the applicant in order to reduce the risk to an acceptable level. If a risk mitigation measure does not fulfil the criteria mentioned above then the outcome of the risk assessment is that a serious risk for the environment exists. In accordance with Directive 2001/82/EC (as amended) this risk has to be weighed against the favourable aspects of a marketing authorization. The prioritization scheme is based on a quantitative approach and consist of different phases. First, for each VMP, PECs are calculated using simple exposure models and worst case assumptions. PNECs are calculated for non-target organisms representative of the considered ecosystems (soil or surface water). Then numerical scores are given to the calculated PEC/PNEC ratio. Finally, the obtained score is multiplied with a further score which is based on the relevance of the metabolic rate in animals. RANKVET can be applied for surface water and soil systems and for different farming methods (intensive or pasture) and treated species. As an example of its potential use we applied RANKVET to 48 VMPs largely utilized in Italy.     

A Bayesian method for comparing and combining binary classifiers in the absence of a gold standard

ABSTRACT: BACKGROUND: Many problems in bioinformatics involve classification based on features such as sequence, structure or morphology. Given multiple classifiers, two crucial questions arise: how does their performance compare, and how can they best be combined to produce a better classifier? A classifier can be evaluated in terms of sensitivity and specificity using benchmark, or gold standard, data, that is, data for which the true classification is known. However, a gold standard is not always available. Here we demonstrate that a Bayesian model for comparing medical diagnostics without a gold standard can be successfully applied in the bioinformatics domain, to genomic scale data sets. We present a new implementation, which unlike previous implementations is applicable to any number of classifiers. We apply this model, for the first time, to the problem of finding the globally optimal logical combination of classifiers. RESULTS: We compared three classifiers of protein subcellular localisation, and evaluated our estimates of sensitivity and specificity against estimates obtained using a gold standard. The method overestimated sensitivity and specificity with only a small discrepancy, and correctly ranked the classifiers. Diagnostic tests for swine flu were then compared on a small data set. Lastly, classifiers for a genome-wide association study of macular degeneration with 541094 SNPs were analysed. In all cases, run times were feasible, and results precise. The optimal logical combination of classifiers was also determined for all three data sets. Code and data are available from http://bioinformatics.monash.edu.au/downloads/. CONCLUSIONS: The examples demonstrate the methods are suitable for both small and large data sets, applicable to the wide range of bioinformatics classification problems, and robust to dependence between classifiers. In all three test cases, the globally optimal logical combination of the classifiers was found to be their union, according to three out of four ranking criteria. We propose as a general rule of thumb that the union of classifiers will be close to optimal.     

A general modeling and visualization tool for comparing different members of a group: application to studying tau-mediated regulation of microtubule dynamics

Background  

Innumerable biological investigations require comparing collections of molecules, cells or organisms to one another with respect to one or more of their properties. Almost all of these comparisons are performed manually, which can be susceptible to inadvertent bias as well as miss subtle effects. The development and application of computer-assisted analytical and interpretive tools could help address these issues and thereby dramatically improve these investigations.     

Performance of reclassification statistics in comparing risk prediction models

Concerns have been raised about the use of traditional measures of model fit in evaluating risk prediction models for clinical use, and reclassification tables have been suggested as an alternative means of assessing the clinical utility of a model. Several measures based on the table have been proposed, including the reclassification calibration (RC) statistic, the net reclassification improvement (NRI), and the integrated discrimination improvement (IDI), but the performance of these in practical settings has not been fully examined. We used simulations to estimate the type I error and power for these statistics in a number of scenarios, as well as the impact of the number and type of categories, when adding a new marker to an established or reference model. The type I error was found to be reasonable in most settings, and power was highest for the IDI, which was similar to the test of association. The relative power of the RC statistic, a test of calibration, and the NRI, a test of discrimination, varied depending on the model assumptions. These tools provide unique but complementary information.     

ROSO: optimizing oligonucleotide probes for microarrays

ROSO is software to design optimal oligonucleotide probe sets for microarrays. Selected probes show no significant cross-hybridization, no stable secondary structures and their Tm are chosen to minimize the Tm variability of the probe set. AVAILABILITY: The program is available on the internet. Sources are freely available, for non-profit use, on request to the authors. Supplementary information: http://pbil.univ-lyon1.fr/roso     

UFFizi: a generic platform for ranking informative features

Background  

Feature selection is an important pre-processing task in the analysis of complex data. Selecting an appropriate subset of features can improve classification or clustering and lead to better understanding of the data. An important example is that of finding an informative group of genes out of thousands that appear in gene-expression analysis. Numerous supervised methods have been suggested but only a few unsupervised ones exist. Unsupervised Feature Filtering (UFF) is such a method, based on an entropy measure of Singular Value Decomposition (SVD), ranking features and selecting a group of preferred ones.     

DOCKSCORE: a webserver for ranking protein-protein docked poses

Background

Proteins interact with a variety of other molecules such as nucleic acids, small molecules and other proteins inside the cell. Structure-determination of protein-protein complexes is challenging due to several reasons such as the large molecular weights of these macromolecular complexes, their dynamic nature, difficulty in purification and sample preparation. Computational docking permits an early understanding of the feasibility and mode of protein-protein interactions. However, docking algorithms propose a number of solutions and it is a challenging task to select the native or near native pose(s) from this pool. DockScore is an objective scoring scheme that can be used to rank protein-protein docked poses. It considers several interface parameters, namely, surface area, evolutionary conservation, hydrophobicity, short contacts and spatial clustering at the interface for scoring.

Results

We have implemented DockScore in form of a webserver for its use by the scientific community. DockScore webserver can be employed, subsequent to docking, to perform scoring of the docked solutions, starting from multiple poses as inputs. The results, on scores and ranks for all the poses, can be downloaded as a csv file and graphical view of the interface of best ranking poses is possible.

Conclusions

The webserver for DockScore is made freely available for the scientific community at: http://caps.ncbs.res.in/dockscore/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0572-6) contains supplementary material, which is available to authorized users.     

CGH-Plotter: MATLAB toolbox for CGH-data analysis

CGH-Plotter is a MATLAB toolbox with a graphical user interface for the analysis of comparative genomic hybridization (CGH) microarray data. CGH-Plotter provides a tool for rapid visualization of CGH-data according to the locations of the genes along the genome. In addition, the CGH-Plotter identifies regions of amplifications and deletions, using k-means clustering and dynamic programming. The application offers a convenient way to analyze CGH-data and can also be applied for the analysis of cDNA microarray expression data. CGH-Plotter toolbox is platform independent and requires MATLAB 6.1 or higher to operate.     

BiVisu: software tool for bicluster detection and visualization

BiVisu is an open-source software tool for detecting and visualizing biclusters embedded in a gene expression matrix. Through the use of appropriate coherence relations, BiVisu can detect constant, constant-row, constant-column, additive-related as well as multiplicative-related biclusters. The biclustering results are then visualized under a 2D setting for easy inspection. In particular, parallel coordinate (PC) plots for each bicluster are displayed, from which objective and subjective cluster quality evaluation can be performed. Availability: BiVisu has been developed in Matlab and is available at http://www.eie.polyu.edu.hk/~nflaw/Biclustering/.     

BugView: a browser for comparing genomes

BugView is a Java application for visualizing homologous genes on a pair of related genomes, and can also be used to view individual genomes. It accepts files of prokaryotic or eukaryotic genomes in GenBank format and allows users to assign homologous pairs, and make and save annotations. AVAILABILITY: http://www.gla.ac.uk/~dpl1n/BugView/     

BicOverlapper: a tool for bicluster visualization

Summary: BicOverlapper is a tool to visualize biclusters fromgene-expression matrices in a way that helps to compare biclusteringmethods, to unravel trends and to highlight relevant genes andconditions. A visual approach can complement biological andstatistical analysis and reduce the time spent by specialistsinterpreting the results of biclustering algorithms. The techniqueis based on a force-directed graph where biclusters are representedas flexible overlapped groups of genes and conditions. Availability: The BicOverlapper software and supplementary materialare available at http://vis.usal.es/bicoverlapper Contact: rodri{at}usal.es Associate Editor: John Quackenbush The first two authors should be reported as joint first authors.     

A role for supplements in optimizing health: the metabolic tune-up

An optimum intake of micronutrients and metabolites, which varies with age and genetic constitution, would tune up metabolism and give a marked increase in health, particularly for the poor, young, obese, and elderly, at little cost. (1) DNA damage. Deficiency of vitamins B-12, folic acid, B-6, C or E, or iron or zinc appears to mimic radiation in damaging DNA by causing single- and double-strand breaks, oxidative lesions or both. Half of the population may be deficient in at least one of these micronutrients. (2) The Km concept. Approximately 50 different human genetic diseases that are due to a poorer binding affinity (Km) of the mutant enzyme for its coenzyme can be remedied by feeding high-dose B vitamins, which raise levels of the corresponding coenzyme. Many polymorphisms also result in a lowered affinity of enzyme for coenzyme. (3) Mitochondrial oxidative decay. This decay, which is a major contributor to aging, can be ameliorated by feeding old rats the normal mitochondrial metabolites acetyl carnitine and lipoic acid at high levels. Many common micronutrient deficiencies, such as iron or biotin, cause mitochondrial decay with oxidant leakage leading to accelerated aging and neural decay.     

SBMLToolbox: an SBML toolbox for MATLAB users

SUMMARY: We present SBMLToolbox, a toolbox that facilitates importing and exporting models represented in the Systems Biology Markup Language (SBML) in and out of the MATLAB environment and provides functionality that enables an experienced user of either SBML or MATLAB to combine the computing power of MATLAB with the portability and exchangeability of an SBML model. SBMLToolbox supports all levels and versions of SBML. AVAILABILITY: SBMLToolbox is freely available from http://sbml.org/software/sbmltoolbox