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1.
BMC Syst Biol ; 10(1): 56, 2016 07 27.
Article in English | MEDLINE | ID: mdl-27460034

ABSTRACT

BACKGROUND: Computational support is essential in order to reason on the dynamics of biological systems. We have developed the software tool ANIMO (Analysis of Networks with Interactive MOdeling) to provide such computational support and allow insight into the complex networks of signaling events occurring in living cells. ANIMO makes use of timed automata as an underlying model, thereby enabling analysis techniques from computer science like model checking. Biology experts are able to use ANIMO via a user interface specifically tailored for biological applications. In this paper we compare the use of ANIMO with some established formalisms on two case studies. RESULTS: ANIMO is a powerful and user-friendly tool that can compete with existing continuous and discrete paradigms. We show this by presenting ANIMO models for two case studies: Drosophila melanogaster circadian clock, and signal transduction events downstream of TNF α and EGF in HT-29 human colon carcinoma cells. The models were originally developed with ODEs and fuzzy logic, respectively. CONCLUSIONS: Two biological case studies that have been modeled with respectively ODE and fuzzy logic models can be conveniently modeled using ANIMO. The ANIMO models require less parameters than ODEs and are more precise than fuzzy logic. For this reason we position the modelling paradigm of ANIMO between ODEs and fuzzy logic.


Subject(s)
Computational Biology/methods , Fuzzy Logic , Software , Animals , Circadian Clocks , Drosophila melanogaster/cytology , Drosophila melanogaster/metabolism , Drosophila melanogaster/physiology , Epidermal Growth Factor/metabolism , HT29 Cells , Humans , Signal Transduction , Tumor Necrosis Factor-alpha/metabolism
2.
Res Integr Peer Rev ; 1: 3, 2016.
Article in English | MEDLINE | ID: mdl-29451542

ABSTRACT

BACKGROUND: In about one in 10,000 cases, a published article is retracted. This very often means that the results it reports are flawed. Several authors have voiced concerns about the presence of retracted research in the memory of science. In particular, a retracted result is propagated by citing it. In the published literature, many instances are given of retracted articles that are cited both before and after their retraction. Even worse is the possibility that these articles in turn are cited in such a way that the retracted result is propagated further. METHODS: We have conducted a case study to find out how a retracted article is cited and whether retracted results are propagated through indirect citations. We have constructed the entire citation network for this case. RESULTS: We show that directly citing articles is an important source of propagation of retracted research results. In contrast, in our case study, indirect citations do not contribute to the propagation of the retracted result. CONCLUSIONS: While admitting the limitations of a study involving a single case, we think there are reasons for the non-contribution of indirect citations that hold beyond our case study.

3.
IEEE J Biomed Health Inform ; 18(3): 832-9, 2014 May.
Article in English | MEDLINE | ID: mdl-24808226

ABSTRACT

Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.


Subject(s)
Models, Biological , Signal Transduction , Systems Biology/methods , Animals , PC12 Cells , Rats , Signal Transduction/genetics , Signal Transduction/physiology , User-Computer Interface
4.
BMC Res Notes ; 2: 138, 2009 Jul 16.
Article in English | MEDLINE | ID: mdl-19607662

ABSTRACT

BACKGROUND: R is the statistical language commonly used by many life scientists in (omics) data analysis. At the same time, these complex analyses benefit from a workflow approach, such as used by the open source workflow management system Taverna. However, Taverna had limited support for R, because it supported just a few data types and only a single output. Also, there was no support for graphical output and persistent sessions. Altogether this made using R in Taverna impractical. FINDINGS: We have developed an R plugin for Taverna: RShell, which provides R functionality within workflows designed in Taverna. In order to fully support the R language, our RShell plugin directly uses the R interpreter. The RShell plugin consists of a Taverna processor for R scripts and an RShell Session Manager that communicates with the R server. We made the RShell processor highly configurable allowing the user to define multiple inputs and outputs. Also, various data types are supported, such as strings, numeric data and images. To limit data transport between multiple RShell processors, the RShell plugin also supports persistent sessions. Here, we will describe the architecture of RShell and the new features that are introduced in version 1.2, i.e.: i) Support for R up to and including R version 2.9; ii) Support for persistent sessions to limit data transfer; iii) Support for vector graphics output through PDF; iv)Syntax highlighting of the R code; v) Improved usability through fewer port types.Our new RShell processor is backwards compatible with workflows that use older versions of the RShell processor. We demonstrate the value of the RShell processor by a use-case workflow that maps oligonucleotide probes designed with DNA sequence information from Vega onto the Ensembl genome assembly. CONCLUSION: Our RShell plugin enables Taverna users to employ R scripts within their workflows in a highly configurable way.

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