Phylogenetic trees: visualizing, customizing and detecting incongruence

Summary: TreeIllustrator is a user-friendly application to visualizeand customize phylogenetic trees. It has a broad range of functionsand capabilities, such as dragging of nodes, different treeshapes, zooming and searching capabilities, and support forlarge trees. It acts as a solution that integrates the specificityof visualizing phylogenetic trees and the customization optionsof a drawing program. It also contains a simple and effectivemethod that compares a custom tree with the Tree of Life, bydetecting incongruence. Availability: A free version is available online at http://nexus.ugent.be/geert/ Contact: wim.vancriekinge{at}ugent.be     

Building blocks for plant gene assembly

The MultiSite Gateway cloning system, based on site-specific recombination, enables the assembly of multiple DNA fragments in predefined order, orientation, and frame register. To streamline the construction of recombinant genes for functional analysis in plants, we have built a collection of 36 reference Gateway entry clones carrying promoters, terminators, and reporter genes, as well as elements of the LhG4/LhGR two-component system. This collection obeys simple engineering rules. The genetic elements (parts) are designed in a standard format. They are interchangeable, fully documented, and can be combined at will according to the desired output. We also took advantage of the MultiSite Gateway recombination sites to create vectors in which two or three genes can be cloned simultaneously in separate expression cassettes. To illustrate the flexibility of these core resources for the construction of a wide variety of plant transformation vectors, we generated various transgenes encoding fluorescent proteins and tested their activity in plant cells. The structure and sequence of all described plasmids are accessible online at http://www.psb.ugent.be/gateway/. All accessions can be requested via the same Web site.     

Modeling biological systems using Dynetica--a simulator of dynamic networks

We present Dynetica, a user-friendly simulator of dynamic networks for constructing, visualizing, and analyzing kinetic models of biological systems. In addition to generic reaction networks, Dynetica facilitates construction of models of genetic networks, where many reactions are gene expression and interactions among gene products. Further, it integrates the capability of conducting both deterministic and stochastic simulations. AVAILABILITY AND SUPPLEMENTARY INFORMATION: Dynetica 1.0, example models, and the user's guide are available at http://www.its.caltech.edu/~you/Dynetica/Dynetica_page.htm     

Gene Time E{chi}pression Warper: a tool for alignment, template matching and visualization of gene expression time series

An application tool for alignment, template matching and visualization of gene expression time series is presented. The core algorithm is based on dynamic time warping techniques used in the speech recognition field. These techniques allow for non-linear (elastic) alignment of temporal sequences of feature vectors and consequently enable detection of similar shapes with different phases. AVAILABILITY: The Java program, examples and a tutorial are available at http://www.psb.ugent.be/cbd/papers/gentxwarper/     

Sigpep: calculating unique peptide signature transition sets in a complete proteome background

We have created a new software platform called sigpep that analyzes transition redundancy in selected reaction monitoring assays. Building on this platform, we also created a web application to generate transition sets with unique signatures for targeted peptides. The platform has been made available under the permissive Apache 2.0 open-source license, and the web application can be accessed from http://iomics.ugent.be/sigpep.     

CyClus3D: a Cytoscape plugin for clustering network motifs in integrated networks

SUMMARY: Network motifs in integrated molecular networks represent functional relationships between distinct data types. They aggregate to form dense topological structures corresponding to functional modules which cannot be detected by traditional graph clustering algorithms. We developed CyClus3D, a Cytoscape plugin for clustering composite three-node network motifs using a 3D spectral clustering algorithm. AVAILABILITY: Via the Cytoscape plugin manager or http://bioinformatics.psb.ugent.be/software/details/CyClus3D.     

PiNGO: a Cytoscape plugin to find candidate genes in biological networks

PiNGO is a tool to screen biological networks for candidate genes, i.e. genes predicted to be involved in a biological process of interest. The user can narrow the search to genes with particular known functions or exclude genes belonging to particular functional classes. PiNGO provides support for a wide range of organisms and Gene Ontology classification schemes, and it can easily be customized for other organisms and functional classifications. PiNGO is implemented as a plugin for Cytoscape, a popular network visualization platform. AVAILABILITY: PiNGO is distributed as an open-source Java package under the GNU General Public License (http://www.gnu.org/), and can be downloaded via the Cytoscape plugin manager. A detailed user guide and tutorial are available on the PiNGO website (http://www.psb.ugent.be/esb/PiNGO.     

STOCHSIM: modelling of stochastic biomolecular processes

SUMMARY: STOCHSIM is a stochastic simulator for chemical reactions. Molecules are represented as individual software objects that react according to probabilities derived from concentrations and rate constants. Version 1.2 of STOCHSIM provides a novel cross-platform graphical interface written in Perl/Tk. A simple two-dimensional spatial structure has also been implemented, in which nearest-neighbour interactions of molecules in a 2-D lattice can be simulated.     

jTraML: an open source Java API for TraML, the PSI standard for sharing SRM transitions

We here present jTraML, a Java API for the Proteomics Standards Initiative TraML data standard. The library provides fully functional classes for all elements specified in the TraML XSD document, as well as convenient methods to construct controlled vocabulary-based instances required to define SRM transitions. The use of jTraML is demonstrated via a two-way conversion tool between TraML documents and vendor specific files, facilitating the adoption process of this new community standard. The library is released as open source under the permissive Apache2 license and can be downloaded from http://jtraml.googlecode.com . TraML files can also be converted online at http://iomics.ugent.be/jtraml .     

Computer simulations: tools for population and evolutionary genetics

Computer simulations are excellent tools for understanding the evolutionary and genetic consequences of complex processes whose interactions cannot be analytically predicted. Simulations have traditionally been used in population genetics by a fairly small community with programming expertise, but the recent availability of dozens of sophisticated, customizable software packages for simulation now makes simulation an accessible option for researchers in many fields. The in silico genetic data produced by simulations, along with greater availability of population-genomics data, are transforming genetic epidemiology, anthropology, evolutionary and population genetics and conservation. In this Review of the state-of-the-art of simulation software, we identify applications of simulations, evaluate simulator capabilities, provide a guide for their use and summarize future directions.     

It’s Time for Some “Site”-Seeing: Novel Tools to Monitor the Ubiquitin Landscape in Arabidopsis thaliana

Ubiquitination, the covalent binding of the small protein modifier ubiquitin to a target protein, is an important and frequently studied posttranslational protein modification. Multiple reports provide useful insights into the plant ubiquitinome, but mostly at the protein level without comprehensive site identification. Here, we implemented ubiquitin combined fractional diagonal chromatography (COFRADIC) for proteome-wide ubiquitination site mapping on Arabidopsis thaliana cell cultures. We identified 3009 sites on 1607 proteins, thereby greatly increasing the number of known ubiquitination sites in this model plant. Finally, The Ubiquitination Site tool (http://bioinformatics.psb.ugent.be/webtools/ubiquitin_viewer/) gives access to the obtained ubiquitination sites, not only to consult the ubiquitination status of a given protein, but also to conduct intricate experiments aiming to study the roles of specific ubiquitination events. Together with the antibodies recognizing the ubiquitin remnant motif, ubiquitin COFRADIC represents a powerful tool to resolve the ubiquitination maps of numerous cellular processes in plants.     

hfAIM: A reliable bioinformatics approach for in silico genome-wide identification of autophagy-associated Atg8-interacting motifs in various organisms

Most of the proteins that are specifically turned over by selective autophagy are recognized by the presence of short Atg8 interacting motifs (AIMs) that facilitate their association with the autophagy apparatus. Such AIMs can be identified by bioinformatics methods based on their defined degenerate consensus F/W/Y-X-X-L/I/V sequences in which X represents any amino acid. Achieving reliability and/or fidelity of the prediction of such AIMs on a genome-wide scale represents a major challenge. Here, we present a bioinformatics approach, high fidelity AIM (hfAIM), which uses additional sequence requirements—the presence of acidic amino acids and the absence of positively charged amino acids in certain positions—to reliably identify AIMs in proteins. We demonstrate that the use of the hfAIM method allows for in silico high fidelity prediction of AIMs in AIM-containing proteins (ACPs) on a genome-wide scale in various organisms. Furthermore, by using hfAIM to identify putative AIMs in the Arabidopsis proteome, we illustrate a potential contribution of selective autophagy to various biological processes. More specifically, we identified 9 peroxisomal PEX proteins that contain hfAIM motifs, among which AtPEX1, AtPEX6 and AtPEX10 possess evolutionary-conserved AIMs. Bimolecular fluorescence complementation (BiFC) results verified that AtPEX6 and AtPEX10 indeed interact with Atg8 in planta. In addition, we show that mutations occurring within or nearby hfAIMs in PEX1, PEX6 and PEX10 caused defects in the growth and development of various organisms. Taken together, the above results suggest that the hfAIM tool can be used to effectively perform genome-wide in silico screens of proteins that are potentially regulated by selective autophagy. The hfAIM system is a web tool that can be accessed at link: http://bioinformatics.psb.ugent.be/hfAIM/.     

Wildfire: distributed, Grid-enabled workflow construction and execution

Background

The availability of the human genome sequence as well as the large number of physically accessible oligonucleotides, cDNA, and BAC clones across the entire genome has triggered and accelerated the use of several platforms for analysis of DNA copy number changes, amongst others microarray comparative genomic hybridization (arrayCGH). One of the challenges inherent to this new technology is the management and analysis of large numbers of data points generated in each individual experiment.

Results

We have developed arrayCGHbase, a comprehensive analysis platform for arrayCGH experiments consisting of a MIAME (Minimal Information About a Microarray Experiment) supportive database using MySQL underlying a data mining web tool, to store, analyze, interpret, compare, and visualize arrayCGH results in a uniform and user-friendly format. Following its flexible design, arrayCGHbase is compatible with all existing and forthcoming arrayCGH platforms. Data can be exported in a multitude of formats, including BED files to map copy number information on the genome using the Ensembl or UCSC genome browser.

Conclusion

ArrayCGHbase is a web based and platform independent arrayCGH data analysis tool, that allows users to access the analysis suite through the internet or a local intranet after installation on a private server. ArrayCGHbase is available at http://medgen.ugent.be/arrayCGHbase/.     

Simulating gene-gene and gene-environment interactions in complex diseases: Gene-Environment iNteraction Simulator 2

ABSTRACT: BACKGROUND: The analysis of complex diseases is an important problem in human genetics. Because multifactoriality isexpected to play a pivotal role, many studies are currently focused on collecting information on the geneticand environmental factors that potentially influence these diseases. However, there is still a lack of efficientand thoroughly tested statistical models that can be used to identify implicated features and theirinteractions. Simulations using large biologically realistic data sets with known gene-gene andgene-environment interactions that influence the risk of a complex disease are a convenient and useful wayto assess the performance of statistical methods. RESULTS: The Gene-Environment iNteraction Simulator 2 (GENS2) simulates interactions among two genetic and oneenvironmental factor and also allows for epistatic interactions. GENS2 is based on data with realisticpatterns of linkage disequilibrium, and imposes no limitations either on the number of individuals to besimulated or on number of non-predisposing genetic/environmental factors to be considered. The GENS2tool is able to simulate gene-environment and gene-gene interactions. To make the Simulator more intuitive,the input parameters are expressed as standard epidemiological quantities. GENS2 is written in Pythonlanguage and takes advantage of operators and modules provided by the simuPOP simulation environment.It can be used through a graphical or a command-line interface and is freely available fromhttp://sourceforge.net/projects/gensim. The software is released under the GNU General Public Licenseversion 3.0. CONCLUSIONS: Data produced by GENS2 can be used as a benchmark for evaluating statistical tools designed for theidentification of gene-gene and gene-environment interactions.