A tool for analyzing information from data storage tags: the continuous wavelet transform (CWT)

Electronic Data Storage Tags (DSTs) have the potential of providing long term, high-resolution observation data of individual fish in the ecosystem. However, traditional time series analysis methods are limited in extracting the required information from DSTs. The continuous wavelet transform (CWT) is a tool for decomposing a time series into instantaneous frequency versus time characteristics. This allows data signals, which are restricted to specific frequencies (localized frequencies), or frequency components, which are restricted to specific time intervals (time localized) to be extracted and displayed in a highly intuitive way. The aim of this short communication is to present the CWT as a tool for extracting information from DST data. In the first case, synthetically generated data is used to demonstrate how the methodology captures different time–frequency dependent patterns in the time series data. The relevance of the methodology to real field data is demonstrated by an analysis of DST depth data from tagged Barents Sea coastal cod. This work has also enjoyed partial funding from the EU-FP5-Q5RS200200813 CODYSSEY project.     

Hawkeye: an interactive visual analytics tool for genome assemblies

Genome sequencing remains an inexact science, and genome sequences can contain significant errors if they are not carefully examined. Hawkeye is our new visual analytics tool for genome assemblies, designed to aid in identifying and correcting assembly errors. Users can analyze all levels of an assembly along with summary statistics and assembly metrics, and are guided by a ranking component towards likely mis-assemblies. Hawkeye is freely available and released as part of the open source AMOS project .     

GPMAW--a software tool for analyzing proteins and peptides.

General Protein/Mass Analysis for Windows (GPMAW) is a valuable piece of software for any molecular biologist, biochemist or mass spectrometrist wishing to analyze protein or peptide sequences. All steps from the acquisition of protein sequence from a built-in web interface, to proteolytic digests, theoretical peptide fragmentation, detailed annotation of sequences and secondary structure prediction, can be performed rapidly and intuitively without first having to spend days reading manuals.     

Ordination as a tool for analyzing complex data sets

Summary Ordination has proven to be a useful tool for examining relationships between environment and vegetation in data sets with a simple underlying environmental strueture. Complex data sets have proven much less tractable. A strategy is offered for dealing with complex data sets based on progressive removal of sets of stands along identified gradients, and subsequent reordination. This strategy is demonstrated using forests of the North Carolina piedmont.The author gratefully acknowledges the continuing collaboration of Dr. Norman L. Christensen of Duke University. This research was supported by National Science Foundation grants DEB-7708743 and DEB-7804043 to R.K.P. and DEB-7707532 and DEB-7804041 to N.L.C.     

Reversal of female mate choice by copying in the guppy (Poecilia reticulata).

Ever since Fisher (1958) formalized models of sexual selection, female mate choice has been assumed to be a genetically determined trait. Females, however, may also use social cues to select mates. One such cue might be the mate choice of conspecifics. Here we report the first direct evidence that a female's preference for a particular male can in fact be reversed by social cues. In our experiments using the Trinidadian guppy (Poecilia reticulata), this reversal was mediated by mate-copying opportunities, such that a female (the 'focal' female) is given the opportunity to choose between two males, followed by a period in which she observes a second female (the 'model' female) displaying a preference for the male she herself did not prefer initially. When allowed to choose between the same males a second time, compared with control tests, a significant proportion of focal females reversed their mate choice and copied the preference of the model female. These results provide strong evidence for the role of non-genetic factors in sexual selection and underlie the need for new models of sexual selection that explicitly incorporate both genetic and cultural aspects of mate choice.     

SCEPTRANS: an online tool for analyzing periodic transcription in yeast

SUMMARY: SCEPTRANS is designed for analysis of microarray timecourse data related to periodic phenomena in the budding yeast. The server allows for easy viewing of temporal profiles of multiple genes in a number of datasets. Additional functionality includes searching for coexpressed genes, periodicity and correlation analysis, integrating functional annotation and localization data as well as advanced operations on sets of genes. AVAILABILITY: Available online at http://sceptrans.org/     

BioSuper: A web tool for the superimposition of biomolecules and assemblies with rotational symmetry

Background

Predicting protein structure from sequence is one of the most significant and challenging problems in bioinformatics. Numerous bioinformatics techniques and tools have been developed to tackle almost every aspect of protein structure prediction ranging from structural feature prediction, template identification and query-template alignment to structure sampling, model quality assessment, and model refinement. How to synergistically select, integrate and improve the strengths of the complementary techniques at each prediction stage and build a high-performance system is becoming a critical issue for constructing a successful, competitive protein structure predictor.

Results

Over the past several years, we have constructed a standalone protein structure prediction system MULTICOM that combines multiple sources of information and complementary methods at all five stages of the protein structure prediction process including template identification, template combination, model generation, model assessment, and model refinement. The system was blindly tested during the ninth Critical Assessment of Techniques for Protein Structure Prediction (CASP9) in 2010 and yielded very good performance. In addition to studying the overall performance on the CASP9 benchmark, we thoroughly investigated the performance and contributions of each component at each stage of prediction.

Conclusions

Our comprehensive and comparative study not only provides useful and practical insights about how to select, improve, and integrate complementary methods to build a cutting-edge protein structure prediction system but also identifies a few new sources of information that may help improve the design of a protein structure prediction system. Several components used in the MULTICOM system are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/.     

Cytogenetics as a tool for triatomine species distinction (Hemiptera-Reduviidae).

Several cytogenetic traits were tested as species diagnostic characters on five triatomine species: Rhodnius pictipes, R. nasutus, R. robustus, Triatoma matogrossensis and T. pseudomaculata. Four of them are described for the first time. The detailed analysis of the meiotic process and the application of C-banding allowed us to identify seven cytogenetic characters which result useful to characterize and differentiate triatomine species.     

Delta plots: a tool for analyzing phylogenetic distance data

A method is described that allows the assessment of treelikeness of phylogenetic distance data before tree estimation. This method is related to statistical geometry as introduced by Eigen, Winkler-Oswatitsch, and Dress (1988 [Proc. Natl. Acad. Sci. USA. 85:5913-5917]), and in essence, displays a measure for treelikeness of quartets in terms of a histogram that we call a delta plot. This allows identification of nontreelike data and analysis of noisy data sets arising from processes such as, for example, parallel evolution, recombination, or lateral gene transfer. In addition to an overall assessment of treelikeness, individual taxa can be ranked by reference to the treelikeness of the quartets to which they belong. Removal of taxa on the basis of this ranking results in an increase in accuracy of tree estimation. Recombinant data sets are simulated, and the method is shown to be capable of identifying single recombinant taxa on the basis of distance information alone, provided the parents of the recombinant sequence are sufficiently divergent and the mixture of tree histories is not strongly skewed toward a single tree. delta Plots and taxon rankings are applied to three biological data sets using distances derived from sequence alignment, gene order, and fragment length polymorphism.     

FISH Finder: a high-throughput tool for analyzing FISH images

MOTIVATION: Fluorescence in situ hybridization (FISH) is used to study the organization and the positioning of specific DNA sequences within the cell nucleus. Analyzing the data from FISH images is a tedious process that invokes an element of subjectivity. Automated FISH image analysis offers savings in time as well as gaining the benefit of objective data analysis. While several FISH image analysis software tools have been developed, they often use a threshold-based segmentation algorithm for nucleus segmentation. As fluorescence signal intensities can vary significantly from experiment to experiment, from cell to cell, and within a cell, threshold-based segmentation is inflexible and often insufficient for automatic image analysis, leading to additional manual segmentation and potential subjective bias. To overcome these problems, we developed a graphical software tool called FISH Finder to automatically analyze FISH images that vary significantly. By posing the nucleus segmentation as a classification problem, compound Bayesian classifier is employed so that contextual information is utilized, resulting in reliable classification and boundary extraction. This makes it possible to analyze FISH images efficiently and objectively without adjustment of input parameters. Additionally, FISH Finder was designed to analyze the distances between differentially stained FISH probes. AVAILABILITY: FISH Finder is a standalone MATLAB application and platform independent software. The program is freely available from: http://code.google.com/p/fishfinder/downloads/list.     

Fluorescently labeled ribosomes as a tool for analyzing antibiotic binding

Measuring the binding of antibiotics and other small-molecular-weight ligands to the 2.5 MDa ribosome often presents formidable challenges. Here, we describe a general method for studying binding of ligands to ribosomes that carry a site-specific fluorescent label covalently attached to one of the ribosomal proteins. As a proof of principle, an environment-sensitive fluorescent group was placed at several specific sites within the ribosomal protein S12. Small ribosomal subunits were reconstituted from native 16S rRNA, individually purified small subunit proteins, and fluorescently labeled S12. The fluorescence characteristics of the reconstituted subunits were affected by several antibiotics, including streptomycin and neomycin, which bind in the vicinity of protein S12. The equilibrium dissociation constants of the drugs obtained using a conventional fluorometer were in good agreement with those observed using previously published methods and with measurements based on the use of radiolabeled streptomycin. The newly developed method is rapid and sensitive, and can be used for determining thermodynamic and kinetic binding characteristics of antibiotics and other small ribosomal ligands. The method can readily be adapted for use in high-throughput screening assays.     

ANOVA-simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data

MOTIVATION: Datasets resulting from metabolomics or metabolic profiling experiments are becoming increasingly complex. Such datasets may contain underlying factors, such as time (time-resolved or longitudinal measurements), doses or combinations thereof. Currently used biostatistics methods do not take the structure of such complex datasets into account. However, incorporating this structure into the data analysis is important for understanding the biological information in these datasets. RESULTS: We describe ASCA, a new method that can deal with complex multivariate datasets containing an underlying experimental design, such as metabolomics datasets. It is a direct generalization of analysis of variance (ANOVA) for univariate data to the multivariate case. The method allows for easy interpretation of the variation induced by the different factors of the design. The method is illustrated with a dataset from a metabolomics experiment with time and dose factors.     

'ANOVA-simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data'

Smilde et al. Bioinformatics (2005), 21(13); 3043–3048 The above paper by Smilde et al. inappropriately quotes results     

Trace metals in Caprella (Crustacea: Amphipoda). A new tool for monitoring pollution in coastal areas?

The main objective of the present study was to evaluate the concentration of trace metals in eight species of Caprella from sites of different degree of pollution along Southern Spain, and compare them with nine additional species of peracaridean crustaceans (5 gammarids, 3 isopods and 1 tanaid) and three molluscs. This is the first comprehensive study of trace metals in caprellids and other peracaridean crustaceans as a baseline work for future research. For most of the metals, values are higher in caprellids than in the rest of peracarideans and molluscs, as Mytilus or Patella, traditionally used as biomonitor in previous studies. Caprellids showed a significant higher range for Cr, Hg and Zn, while molluscs were better biomonitors for Pb; non-caprellid peracarids showed lower range of Fe and Ni than caprellids and molluscs. Besides the wider ranges shown by caprellids for trace metals in comparison with other invertebrates, Caprella spp. is especially abundant in intertidal and shallow waters ecosystems worldwide; this genus includes species characterised by a short generation time, and a sedentary way of life as a consequence of direct development and low capacity of swimming. Consequently, the use of Caprella spp. could be an interesting tool in monitoring programmes of heavy metal pollution.     

miRspring: a compact standalone research tool for analyzing miRNA-seq data

High-throughput sequencing for microRNA (miRNA) profiling has revealed a vast complexity of miRNA processing variants, but these are difficult to discern for those without bioinformatics expertise and large computing capability. In this article, we present miRNA Sequence Profiling (miRspring) (http://mirspring.victorchang.edu.au), a software solution that creates a small portable research document that visualizes, calculates and reports on the complexities of miRNA processing. We designed an index-compression algorithm that allows the miRspring document to reproduce a complete miRNA sequence data set while retaining a small file size (typically <3 MB). Through analysis of 73 public data sets, we demonstrate miRspring’s features in assessing quality parameters, miRNA cluster expression levels and miRNA processing. Additionally, we report on a new class of miRNA variants, which we term seed-isomiRs, identified through the novel visualization tools of the miRspring document. Further investigation identified that ∼30% of human miRBase entries are likely to have a seed-isomiR. We believe that miRspring will be a highly useful research tool that will enhance the analysis of miRNA data sets and thus increase our understanding of miRNA biology.     

ConvAn: a convergence analyzing tool for optimization of biochemical networks

Dynamic models of biochemical networks usually are described as a system of nonlinear differential equations. In case of optimization of models for purpose of parameter estimation or design of new properties mainly numerical methods are used. That causes problems of optimization predictability as most of numerical optimization methods have stochastic properties and the convergence of the objective function to the global optimum is hardly predictable. Determination of suitable optimization method and necessary duration of optimization becomes critical in case of evaluation of high number of combinations of adjustable parameters or in case of large dynamic models. This task is complex due to variety of optimization methods, software tools and nonlinearity features of models in different parameter spaces. A software tool ConvAn is developed to analyze statistical properties of convergence dynamics for optimization runs with particular optimization method, model, software tool, set of optimization method parameters and number of adjustable parameters of the model. The convergence curves can be normalized automatically to enable comparison of different methods and models in the same scale. By the help of the biochemistry adapted graphical user interface of ConvAn it is possible to compare different optimization methods in terms of ability to find the global optima or values close to that as well as the necessary computational time to reach them. It is possible to estimate the optimization performance for different number of adjustable parameters. The functionality of ConvAn enables statistical assessment of necessary optimization time depending on the necessary optimization accuracy. Optimization methods, which are not suitable for a particular optimization task, can be rejected if they have poor repeatability or convergence properties. The software ConvAn is freely available on www.biosystems.lv/convan.     

SCOPExplorer: a tool for browsing and analyzing structural classification of proteins (SCOP) data

We have developed a tool, named "SCOPExplorer", for browsing and analyzing SCOP information. SCOPExplorer 1) contains a tree-style viewer to display an overview of protein structure data, 2) is able to employ a variety of options to analyze SCOP data statistically, and 3) provides a function to link protein domains to protein data bank (PDB) resources. SCOPExplorer uses an XML-based structural document format, named "SCOPML", derived from the SCOP data. To evaluate SCOPExplorer, proteins containing more than 20 domains were analyzed. The Skp1-Skp2 protein complex and the Fab fragment of IgG2 contain the largest numbers of domains in the current eukaryotic SCOP database. These proteins are known to either bind to various proteins or generate diversity. This suggests that the more domains a protein has, the more interactions or more variability it will be capable of. (SCOPExplorer is available for download at http://scopexplorer.ulsan.ac.kr).