Work flows in life science

The introduction of computer science technology in the life science domain has resulted in a new life science discipline called bioinformatics. Bioinformaticians are biologists who know how to apply computer science technology to perform computer based experiments, also known as in-silico or dry lab experiments. Various tools, such as databases, web applications and scripting languages, are used to design and run in-silico experiments. As the size and complexity of these experiments grow, new types of tools are required to design and execute the experiments and to analyse the results. Workflow systems promise to fulfill this role. The bioinformatician composes an experiment by using tools and web services as building blocks, and connecting them, often through a graphical user interface. Workflow systems, such as Taverna, provide access to up to a few thousand resources in a uniform way. Although workflow systems are intended to make the bioinformaticians' work easier, bioinformaticians experience difficulties in using them. This thesis is devoted to find out which problems bioinformaticians experience using workflow systems and to provide solutions for these problems.\u

In the Truman show: generating dynamic scenarios in a driving simulator

All the devices, animals, and people make their decisions based on what you're doing, but you don't know it or even notice it. Your world is that of Truman Burbank, from the 1998 movie The Truman Show. With this idea in mind, we've taken the movie metaphor to implement a prototype simulation system where the user steps into Truman's shoes. The set of our "movie" is a driving simulator, and the user is learning to drive a car. During the driving lessons, users drive in a virtual world that lets them experience all kinds of traffic scenarios. The system generates the scenarios with the student as the focal point, and the other traffic entities respond to the student's behavior, without the student noticing. To control the traffic scenarios and make them more effective, our prototype employs an agent-based framework. In this framework, each entity in the simulator is an actor agent playing a role. The prototype also includes a hierarchy of directors that directs the main action and the behind-the-scenes activity. The advantage of the movie metaphor is that it helps separate scenario description from scenario playing. The agents can read their required information from a script and perform their actions based on that information. Using this framework lets us build software that's extensible, maintainable, and easy to understan

Using R in Taverna: RShell v1.2

Background: R is the statistical language commonly used by many life scientists in (omics) data 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.\ud \ud 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.\ud \ud Conclusion: Our RShell plugin enables Taverna users to employ R scripts within their workflows in a highly configurable way

Smart Environments for Collaborative Design, Implementation, and Interpretation of Scientific Experiments

Ambient intelligence promises to enable humans to smoothly interact with their environment, mediated by computer technology. In the literature on ambient intelligence, empirical scientists are not often mentioned. Yet they form an interesting target group for this technology. In this position paper, we describe a project aimed at realising an ambient intelligence environment for face-to-face meetings of researchers with different academic backgrounds involved in molecular biology “omics” experiments. In particular, microarray experiments are a focus of attention because these experiments require multidisciplinary collaboration for their design, analysis, and interpretation. Such an environment is characterised by a high degree of complexity that has to be mitigated by ambient intelligence technology. By experimenting in a real-life setting, we will learn more about life scientists as a user group

Performing statistical analyses on quantitative data in Taverna workflows: an example using R and maxdBrowse to identify differentially-expressed genes from microarray data.

BACKGROUND: There has been a dramatic increase in the amount of quantitative data derived from the measurement of changes at different levels of biological complexity during the post-genomic era. However, there are a number of issues associated with the use of computational tools employed for the analysis of such data. For example, computational tools such as R and MATLAB require prior knowledge of their programming languages in order to implement statistical analyses on data. Combining two or more tools in an analysis may also be problematic since data may have to be manually copied and pasted between separate user interfaces for each tool. Furthermore, this transfer of data may require a reconciliation step in order for there to be interoperability between computational tools. RESULTS: Developments in the Taverna workflow system have enabled pipelines to be constructed and enacted for generic and ad hoc analyses of quantitative data. Here, we present an example of such a workflow involving the statistical identification of differentially-expressed genes from microarray data followed by the annotation of their relationships to cellular processes. This workflow makes use of customised maxdBrowse web services, a system that allows Taverna to query and retrieve gene expression data from the maxdLoad2 microarray database. These data are then analysed by R to identify differentially-expressed genes using the Taverna RShell processor which has been developed for invoking this tool when it has been deployed as a service using the RServe library. In addition, the workflow uses Beanshell scripts to reconcile mismatches of data between services as well as to implement a form of user interaction for selecting subsets of microarray data for analysis as part of the workflow execution. A new plugin system in the Taverna software architecture is demonstrated by the use of renderers for displaying PDF files and CSV formatted data within the Taverna workbench. CONCLUSION: Taverna can be used by data analysis experts as a generic tool for composing ad hoc analyses of quantitative data by combining the use of scripts written in the R programming language with tools exposed as services in workflows. When these workflows are shared with colleagues and the wider scientific community, they provide an approach for other scientists wanting to use tools such as R without having to learn the corresponding programming language to analyse their own data.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

<i>GRIN2A</i>-related disorders:genotype and functional consequence predict phenotype

Alterations of the N-methyl-d-aspartate receptor (NMDAR) subunit GluN2A, encoded by GRIN2A, have been associated with a spectrum of neurodevelopmental disorders with prominent speech-related features, and epilepsy. We performed a comprehensive assessment of phenotypes with a standardized questionnaire in 92 previously unreported individuals with GRIN2A-related disorders. Applying the criteria of the American College of Medical Genetics and Genomics to all published variants yielded 156 additional cases with pathogenic or likely pathogenic variants in GRIN2A, resulting in a total of 248 individuals. The phenotypic spectrum ranged from normal or near-normal development with mild epilepsy and speech delay/apraxia to severe developmental and epileptic encephalopathy, often within the epilepsy-aphasia spectrum. We found that pathogenic missense variants in transmembrane and linker domains (misTMD+Linker) were associated with severe developmental phenotypes, whereas missense variants within amino terminal or ligand-binding domains (misATD+LBD) and null variants led to less severe developmental phenotypes, which we confirmed in a discovery (P = 10-6) as well as validation cohort (P = 0.0003). Other phenotypes such as MRI abnormalities and epilepsy types were also significantly different between the two groups. Notably, this was paralleled by electrophysiology data, where misTMD+Linker predominantly led to NMDAR gain-of-function, while misATD+LBD exclusively caused NMDAR loss-of-function. With respect to null variants, we show that Grin2a+/- cortical rat neurons also had reduced NMDAR function and there was no evidence of previously postulated compensatory overexpression of GluN2B. We demonstrate that null variants and misATD+LBD of GRIN2A do not only share the same clinical spectrum (i.e. milder phenotypes), but also result in similar electrophysiological consequences (loss-of-function) opposing those of misTMD+Linker (severe phenotypes; predominantly gain-of-function). This new pathomechanistic model may ultimately help in predicting phenotype severity as well as eligibility for potential precision medicine approaches in GRIN2A-related disorders

Designing Workflows on the Fly Using e-BioFlow

Abstract. Life scientists use workflow systems for service orchestration to design their computer based experiments. These workflow systems require life scientists to design complete workflows before they can be run. Traditional workflow systems not support the explorative research approach life scientists prefer. In life science, it often happens that few steps are known in advance. Even if these steps are known, connecting these tasks still remains difficult.\ud We have extended the e-BioFlow workflow system with an ad-hoc editor to support on-the-fly workflow design. This ad-hoc editor enables an ad-hoc design of the workflow with no predetermined plan of the final workflow. Users can execute partial workflows and extend these workflows using intermediate results. The ad-hoc editor enables its users to explore data and tasks representing tools and web services, in order to debug the workflow and to optimise parameter settings. Furthermore, it guides its users to find and connect compatible tasks. The result is a new workflow editor that simplifies workflow design and\u