SBMLeditor: effective creation of models in the Systems Biology Markup Language (SBML)

Background  

The need to build a tool to facilitate the quick creation and editing of models encoded in the Systems Biology Markup language (SBML) has been growing with the number of users and the increased complexity of the language. SBMLeditor tries to answer this need by providing a very simple, low level editor of SBML files. Users can create and remove all the necessary bits and pieces of SBML in a controlled way, that maintains the validity of the final SBML file.     

cPath: open source software for collecting, storing, and querying biological pathways

Background  

Biological pathways, including metabolic pathways, protein interaction networks, signal transduction pathways, and gene regulatory networks, are currently represented in over 220 diverse databases. These data are crucial for the study of specific biological processes, including human diseases. Standard exchange formats for pathway information, such as BioPAX, CellML, SBML and PSI-MI, enable convenient collection of this data for biological research, but mechanisms for common storage and communication are required.     

Flexible mapping of homology onto structure with Homolmapper

Background  

Over the past decade, a number of tools have emerged for the examination of homology relationships among protein sequences in a structural context. Most recent software implementations for such analysis are tied to specific molecular viewing programs, which can be problematic for collaborations involving multiple viewing environments. Incorporation into larger packages also adds complications for users interested in adding their own scoring schemes or in analyzing proteins incorporating unusual amino acid residues such as selenocysteine.     

KEGGconverter: a tool for the in-silico modelling of metabolic networks of the KEGG Pathways database

Background  

The KEGG Pathway database is a valuable collection of metabolic pathway maps. Nevertheless, the production of simulation capable metabolic networks from KEGG Pathway data is a challenging complicated work, regardless the already developed tools for this scope. Originally used for illustration purposes, KEGG Pathways through KGML (KEGG Markup Language) files, can provide complete reaction sets and introduce species versioning, which offers advantages for the scope of cellular metabolism simulation modelling. In this project, KEGGconverter is described, implemented also as a web-based application, which uses as source KGML files, in order to construct integrated pathway SBML models fully functional for simulation purposes.     

Influence of 5 major Salmonella pathogenicity islands on NK cell depletion in mice infected with <Emphasis Type="Italic">Salmonella enterica</Emphasis> serovar Enteritidis

Background  

In this study we were interested in the colonisation and early immune response of Balb/C mice to infection with Salmonella Enteritidis and isogenic pathogenicity island free mutants.     

Gene capture prediction and overlap estimation in EST sequencing from one or multiple libraries

Background  

In expressed sequence tag (EST) sequencing, we are often interested in how many genes we can capture in an EST sample of a targeted size. This information provides insights to sequencing efficiency in experimental design, as well as clues to the diversity of expressed genes in the tissue from which the library was constructed.     

MassSorter: a tool for administrating and analyzing data from mass spectrometry experiments on proteins with known amino acid sequences

Background  

Proteomics is the study of the proteome, and is critical to the understanding of cellular processes. Two central and related tasks of proteomics are protein identification and protein characterization. Many small laboratories are interested in the characterization of a small number of proteins, e.g., how posttranslational modifications change under different conditions.     

An in silico model of the ubiquitin-proteasome system that incorporates normal homeostasis and age-related decline

Background  

The ubiquitin-proteasome system is responsible for homeostatic degradation of intact protein substrates as well as the elimination of damaged or misfolded proteins that might otherwise aggregate. During ageing there is a decline in proteasome activity and an increase in aggregated proteins. Many neurodegenerative diseases are characterised by the presence of distinctive ubiquitin-positive inclusion bodies in affected regions of the brain. These inclusions consist of insoluble, unfolded, ubiquitinated polypeptides that fail to be targeted and degraded by the proteasome. We are using a systems biology approach to try and determine the primary event in the decline in proteolytic capacity with age and whether there is in fact a vicious cycle of inhibition, with accumulating aggregates further inhibiting proteolysis, prompting accumulation of aggregates and so on. A stochastic model of the ubiquitin-proteasome system has been developed using the Systems Biology Mark-up Language (SBML). Simulations are carried out on the BASIS (Biology of Ageing e-Science Integration and Simulation) system and the model output is compared to experimental data wherein levels of ubiquitin and ubiquitinated substrates are monitored in cultured cells under various conditions. The model can be used to predict the effects of different experimental procedures such as inhibition of the proteasome or shutting down the enzyme cascade responsible for ubiquitin conjugation.     

An integrated network visualization framework towards metabolic engineering applications

Background

Over the last years, several methods for the phenotype simulation of microorganisms, under specified genetic and environmental conditions have been proposed, in the context of Metabolic Engineering (ME). These methods provided insight on the functioning of microbial metabolism and played a key role in the design of genetic modifications that can lead to strains of industrial interest. On the other hand, in the context of Systems Biology research, biological network visualization has reinforced its role as a core tool in understanding biological processes. However, it has been scarcely used to foster ME related methods, in spite of the acknowledged potential.

Results

In this work, an open-source software that aims to fill the gap between ME and metabolic network visualization is proposed, in the form of a plugin to the OptFlux ME platform. The framework is based on an abstract layer, where the network is represented as a bipartite graph containing minimal information about the underlying entities and their desired relative placement. The framework provides input/output support for networks specified in standard formats, such as XGMML, SBGN or SBML, providing a connection to genome-scale metabolic models. An user-interface makes it possible to edit, manipulate and query nodes in the network, providing tools to visualize diverse effects, including visual filters and aspect changing (e.g. colors, shapes and sizes). These tools are particularly interesting for ME, since they allow overlaying phenotype simulation results or elementary flux modes over the networks.

Conclusions

The framework and its source code are freely available, together with documentation and other resources, being illustrated with well documented case studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0420-0) contains supplementary material, which is available to authorized users.     

A manually curated database of tetrapod mitochondrially encoded tRNA sequences and secondary structures

Background  

Mitochondrial tRNAs have been the subject of study for structural biologists interested in their secondary structure characteristics, evolutionary biologists have researched patterns of compensatory and structural evolution and medical studies have been directed towards understanding the basis of human disease. However, an up to date, manually curated database of mitochondrially encoded tRNAs from higher animals is currently not available.     

Ku86 exists as both a full-length and a protease-sensitive natural variant in multiple myeloma cells

Background  

Truncated variants of Ku86 protein have previously been detected in 86% to 100% of freshly isolated patient multiple myeloma (MM) cells. Since, the Ku70/Ku86 heterodimer functions as the regulatory subunit of the DNA repair enzyme, DNA-dependent protein kinase, we have been interested in the altered expression and function of Ku86 variant (Ku86v) proteins in genome maintenance of MM.     

FCI: an R-based algorithm for evaluating uncertainty of absolute real-time PCR quantification

Background  

FCI is an R code for analyzing data from real-time PCR experiments. This algorithm estimates standard curve features as well as nucleic acid concentrations and confidence intervals according to Fieller's theorem.     

An image processing approach to computing distances between RNA secondary structures dot plots

Background  

In phylogenetic inference one is interested in obtaining samples from the posterior distribution over the tree space on the basis of some observed DNA sequence data. One of the simplest sampling methods is the rejection sampler due to von Neumann. Here we introduce an auto-validating version of the rejection sampler, via interval analysis, to rigorously draw samples from posterior distributions over small phylogenetic tree spaces.     

OnEX: Exploring changes in life science ontologies

Background  

Numerous ontologies have recently been developed in life sciences to support a consistent annotation of biological objects, such as genes or proteins. These ontologies underlie continuous changes which can impact existing annotations. Therefore, it is valuable for users of ontologies to study the stability of ontologies and to see how many and what kind of ontology changes occurred.     

sdef: an R package to synthesize lists of significant features in related experiments

Background  

In microarray studies researchers are often interested in the comparison of relevant quantities between two or more similar experiments, involving different treatments, tissues, or species. Typically each experiment reports measures of significance (e.g. p-values) or other measures that rank its features (e.g genes). Our objective is to find a list of features that are significant in all experiments, to be further investigated. In this paper we present an R package called sdef, that allows the user to quantify the evidence of communality between the experiments using previously proposed statistical methods based on the ranked lists of p-values. sdef implements two approaches that address this objective: the first is a permutation test of the maximal ratio of observed to expected common features under the hypothesis of independence between the experiments. The second approach, set in a Bayesian framework, is more flexible as it takes into account the uncertainty on the number of genes differentially expressed in each experiment.     

Reversing expansion of Calamagrostis epigejos in a grassland biodiversity hotspot: Hemiparasitic Rhinanthus major does a better job than increased mowing intensity

Questions

Can hemiparasitic Rhinanthus major originating from a local population suppress the competitive clonal grass Calamagrostis epigejos and reverse its expansion in species‐rich semi‐natural grasslands? Does sowing seeds of R. major facilitate restoration of target meadow vegetation? Is R. major more beneficial for biodiversity restoration/conservation than increased mowing intensity, a conventional measure to suppress C. epigejos?

Location

?ertoryje National Nature Reserve, Bílé Karpaty (White Carpathians) Protected Landscape Area, Czech Republic.

Methods

We conducted a before‐after‐control‐impact experiment in meadow patches heavily infested by C. epigejos: eight blocks, each containing four plots with four treatment combinations: (1) traditional management, i.e. mowing once in summer, (2) mowing in summer and autumn (3) mowing in summer and seed sowing of R. major, (4) mowing in summer and autumn and seed sowing of R. major. Above‐ground biomass of C. epigejos and vegetation composition of each of the plots were monitored every year from 2013 to 2016. To assess the effects of treatments, we analysed biomass production of C. epigejos, herb layer cover and vegetation composition.

Results

Both sowing R. major and an additional autumn meadow cut significantly suppressed C. epigejos. Their effects were additive and of comparable size. Both treatments also had significant but markedly different effects on community composition. Rhinanthus major facilitated directional community composition change towards the regional Brachypodio‐Molinetum meadows. In contrast, increased mowing intensity significantly decreased frequency of threatened species, which however may have also been influenced by R. major.

Conclusions

Sowing of autochthonous R. major seeds was demonstrated as an efficient tool to suppress C. epigejos and facilitate community restoration. It can be combined with an additional meadow cut to further accelerate decline of the grass. The additional cut should however be used as a short‐term practice (1–2 years) only to minimize potential negative effects of its long‐term application on some threatened plant species. The effects of R. major are comparable to those of Rhinanthus alectorolophus reported previously. As a species occurring naturally in species‐rich dry grasslands, R. major has a broader and longer‐term application potential than R. alectorolophus in ecological restoration and conservation of these communities.     

OligoSpawn: a software tool for the design of overgo probes from large unigene datasets

Background  

Expressed sequence tag (EST) datasets represent perhaps the largest collection of genetic information. ESTs can be exploited in a variety of biological experiments and analysis. Here we are interested in the design of overlapping oligonucleotide (overgo) probes from large unigene (EST-contigs) datasets.     

Automating dChip: toward reproducible sharing of microarray data analysis

Background  

During the past decade, many software packages have been developed for analysis and visualization of various types of microarrays. We have developed and maintained the widely used dChip as a microarray analysis software package accessible to both biologist and data analysts. However, challenges arise when dChip users want to analyze large number of arrays automatically and share data analysis procedures and parameters. Improvement is also needed when the dChip user support team tries to identify the causes of reported analysis errors or bugs from users.