A computational workflow for the automated generation of models of genetic designs

Computational models are essential to engineer predictable biological systems and to scale up this process for complex systems. Computational modelling often requires expert knowledge and data to build models. Clearly, manual creation of models is not scalable for large designs. Despite several automated model construction approaches, computational methodologies to bridge knowledge in design repositories and the process of creating computational models has still not been established. This paper describes a workflow for automatic generation of computational models of genetic circuits from data stored in design repositories using existing standards. This workflow leverages the software tool SBOLDesigner to build structural models that are then enriched by the Virtual Parts Repository API using Systems Biology Open Language (SBOL) data fetched from the SynBioHub design repository. The iBioSim software tool is then utilized to convert this SBOL description into a computational model encoding using the Systems Biology Markup Language (SBML). Finally, this SBML model can be simulated using a variety of methods. This workflow provides synthetic biologists with easy to use tools to create predictable biological systems, hiding away the complexity of building computational models. This approach can further be incorporated into other computational workflows for design automation

Extending Greenstone for Institutional Repositories

We examine the problem of designing a generalized system for building institutional repositories. Widely used schemes such as DSpace are tailored to a particular set of requirements: fixed metadata set; standard view when searching and browsing; pre-determined sequence for depositing items; built-in workflow for vetting new items. In contrast, Fedora builds in flexibility: institutional repositories are just one possible instantiation—however generality incurs a high overhead and uptake has been sluggish. This paper shows how existing components of the Greenstone software can be repurposed to provide a generalized institutional repository that falls between these extremes

HyDRA Hybrid workflow Design Recommender Architecture

Workflows are a way to describe a series of computations on raw e-Science data. These data may be MRI brain scans, data from a high energy physics detector or metric data from an earth observation project. In order to derive meaningful knowledge from the data, it must be processed and analysed. Workflows have emerged as the principle mechanism for describing and enacting complex e-Science analyses on distributed infrastructures such as grids. Scientific users face a number of challenges when designing workflows. These challenges include selecting appropriate components for their tasks, spec- ifying dependencies between them and selecting appropriate parameter values. These tasks become especially challenging as workflows become increasingly large. For example, the CIVET workflow consists of up to 108 components. Building the workflow by hand and specifying all the links can become quite cumbersome for scientific users.Traditionally, recommender systems have been employed to assist users in such time-consuming and tedious tasks. One of the techniques used by recommender systems has been to predict what the user is attempting to do using a variety of techniques. These techniques include using workflow se- mantics on the one hand and historical usage patterns on the other. Semantics-based systems attempt to infer a user’s intentions based on the available semantics. Pattern-based systems attempt to extract usage patterns from previously-constructed workflows and match those patterns to the workflow un- der construction. The use of historical patterns adds dynamism to the suggestions as the system can learn and adapt with “experience”. However, in cases where there are no previous patterns to draw upon, pattern-based systems fail to perform. Semantics-based systems, on the other hand infer from static information, so they always have something to draw upon. However, that information first has to be encoded into the semantic repository for the system to draw upon it, which is a time-consuming and tedious task in it self. Moreover, semantics-based systems do not learn and adapt with experience. Both approaches have distinct, but complementary features and drawbacks. By combining the two approaches, the drawbacks of each approach can be addressed.This thesis presents HyDRA, a novel hybrid framework that combines frequent usage patterns and workflow semantics to generate suggestions. The functions performed by the framework include; a) extracting frequent functional usage patterns; b) identifying the semantics of unknown components; and c) generating accurate and meaningful suggestions. Challenges to mining frequent patterns in- clude ensuring that meaningful and useful patterns are extracted. For this purpose only patterns that occur above a minimum frequency threshold are mined. Moreover, instead of just groups of specific components, the pattern mining algorithm takes into account workflow component semantics. This allows the system to identify different types of components that perform a single composite function. One of the challenges in maintaining a semantic repository is to keep the repository up-to-date. This involves identifying new items and inferring their semantics. In this regard, a minor contribution of this research is a semantic inference engine that is responsible for function b). This engine also uses pre-defined workflow component semantics to infer new semantic properties and generate more accurate suggestions. The overall suggestion generation algorithm is also presented.HyDRA has been evaluated using workflows from the Laboratory of Neuro Imaging (LONI) repos- itory. These workflows have been chosen for their structural and functional characteristics that help� to evaluate the framework in different scenarios. The system is also compared with another existing pattern-based system to show a clear improvement in the accuracy of the suggestions generated

Mounting Books Project

4th International Conference on Open RepositoriesThis presentation was part of the session : Conference PresentationsDate: 2009-05-19 03:00 PM – 04:30 PMThe Northwestern University Library undertook a software development project to create an automated workflow to enable files from its Kirtas book scanner to be both linked to the OPAC with a page viewer application, and ingested into its Fedora repository as archivally sustainable and reusable digital objects. The web-based Book Workflow Interface (BWI) software utilizes jBPM for management and web services for key creation components. It also features an AJAX interface to support drag-and-drop creation and editing of METS-based book structures. The BWI system ingests locally scanned texts as well as texts digitized by external partners or vendors. This project addressed the need for a Fedora-based book viewing tool that can be used by other research libraries developing digital repositories based on a Fedora systems architecture. The book view interface includes full-text search and view, search-within-a-book, book structure browse, page turning, and zooming interface components. The workflow system can be expanded over time to support new functions in the book publishing process, and can be redeployed in support of digitization processes for other types of media. Shifting from a simple book reformatting operation to a dynamic program that makes any multipage text object fully accessible online, this system dramatically improves Northwestern's ability to share its unique library and archival collections. The project was fully supported by the Andrew W. Mellon Foundation and the Book Workflow Interface and public book viewing software will both be released as open source in spring 2009.Andrew W. Mellon Foundatio

TumorML: Concept and requirements of an in silico cancer modelling markup language

This paper describes the initial groundwork carried out as part of the European Commission funded Transatlantic Tumor Model Repositories project, to develop a new markup language for computational cancer modelling, TumorML. In this paper we describe the motivations for such a language, arguing that current state-of-the-art biomodelling languages are not suited to the cancer modelling domain. We go on to describe the work that needs to be done to develop TumorML, the conceptual design, and a description of what existing markup languages will be used to compose the language specification

GRIDCC: Real-time workflow system

The Grid is a concept which allows the sharing of resources between distributed communities, allowing each to progress towards potentially different goals. As adoption of the Grid increases so are the activities that people wish to conduct through it. The GRIDCC project is a European Union funded project addressing the issues of integrating instruments into the Grid. This increases the requirement of workflows and Quality of Service upon these workflows as many of these instruments have real-time requirements. In this paper we present the workflow management service within the GRIDCC project which is tasked with optimising the workflows and ensuring that they meet the pre-defined QoS requirements specified upon them

Equal partners? Improving the integration between DSpace and Symplectic Elements

While self-submission by academics was regarded as the ideal way to add content to Open Repositories in the early days of such systems, the reality today is that many institutional repositories obtain their content automatically from integration with research management systems. The institutional DSpace repositories at Auckland University of Technology (AUT) and at the University of Waikato (UoW) were integrated with Symplectic Elements in 2010 (AUT) and in 2014 (UoW). Initial experiences at AUT suggested a mismatch between the interaction options offered to users of Symplectic Elements on one hand and the actions available to repository managers via the DSpace review workflow functionality on the other hand. Our presentation explores these mismatches and their negative effects on the repository as well as on the user experience. We then present the changes we made to the DSpace review workflow to improve the integration. We hope that our experiences will contribute to an improvement in the integration between repository software and research management systems

Collaborative Development and Evaluation of Text-processing Workflows in a UIMA-supported Web-based Workbench

Challenges in creating comprehensive text-processing worklows include a lack of the interoperability of individual components coming from different providers and/or a requirement imposed on the end users to know programming techniques to compose such workflows. In this paper we demonstrate Argo, a web-based system that addresses these issues in several ways. It supports the widely adopted Unstructured Information Management Architecture (UIMA), which handles the problem of interoperability; it provides a web browser-based interface for developing workflows by drawing diagrams composed of a selection of available processing components; and it provides novel user-interactive analytics such as the annotation editor which constitutes a bridge between automatic processing and manual correction. These features extend the target audience of Argo to users with a limited or no technical background. Here, we focus specifically on the construction of advanced workflows, involving multiple branching and merging points, to facilitate various comparative evalutions. Together with the use of user-collaboration capabilities supported in Argo, we demonstrate several use cases including visual inspections, comparisions of multiple processing segments or complete solutions against a reference standard, inter-annotator agreement, and shared task mass evaluations. Ultimetely, Argo emerges as a one-stop workbench for defining, processing, editing and evaluating text processing tasks