Developing integrated workflows for the digitisation of herbarium specimens using a modular and scalable approach

Digitisation programmes in many institutes frequently involve disparate and irregular funding, diverse selection criteria and scope, with different members of staff managing and operating the processes. These factors have influenced the decision at the Royal Botanic Garden Edinburgh to develop an integrated workflow for the digitisation of herbarium specimens which is modular and scalable to enable a single overall workflow to be used for all digitisation projects. This integrated workflow is comprised of three principal elements: a specimen workflow, a data workflow and an image workflow.The specimen workflow is strongly linked to curatorial processes which will impact on the prioritisation, selection and preparation of the specimens. The importance of including a conservation element within the digitisation workflow is highlighted. The data workflow includes the concept of three main categories of collection data: label data, curatorial data and supplementary data. It is shown that each category of data has its own properties which influence the timing of data capture within the workflow. Development of software has been carried out for the rapid capture of curatorial data, and optical character recognition (OCR) software is being used to increase the efficiency of capturing label data and supplementary data. The large number and size of the images has necessitated the inclusion of automated systems within the image workflow.     

Trust-driven and QoS demand clustering analysis based cloud workflow scheduling strategies

Due to the restrictions that most traditional scheduling strategies only cared about users’ quality of service (QoS) time or cost requirements, lacked the effective analysis of users’ real service demand and could not guarantee scheduling security, this paper added trust into workflow’s QoS target and proposed a novel customizable cloud workflow scheduling model. In order to better analyze different user’s service requirements and provide customizable services, the new model divided workflow scheduling into two stages: the macro multi-workflow scheduling as the unit of cloud user and the micro single workflow scheduling. It introduced trust mechanism into multi-workflow scheduling level. And in single workflow scheduling level, it classified workflows into time-sensitive, cost-sensitive and balance three types according to different workflow’s QoS demand parameters using fuzzy clustering method. Based on it, it customized different service strategies for different type. The simulation experiments show that the new schema has some advantages in shortening workflow’s final completion time, achieving relatively high execution success rate and user satisfaction compared to other kindred solutions.     

Workflow management system based on WEB technology

Through the analysis of workflow management system based on Web, the work, following WFMC workflow model, proposed a universal workflow management system with the combination of specific application requirements of enterprises. Workflow management system based on Web was described from system function, software structure, system structure, workflow engine and security. The actual case of the design of aeronautical structure showed that workflow system performance can be greatly improved by using Web technology.     

Standardizing clinical trials workflow representation in UML for international site comparison

Background

With the globalization of clinical trials, a growing emphasis has been placed on the standardization of the workflow in order to ensure the reproducibility and reliability of the overall trial. Despite the importance of workflow evaluation, to our knowledge no previous studies have attempted to adapt existing modeling languages to standardize the representation of clinical trials. Unified Modeling Language (UML) is a computational language that can be used to model operational workflow, and a UML profile can be developed to standardize UML models within a given domain. This paper''s objective is to develop a UML profile to extend the UML Activity Diagram schema into the clinical trials domain, defining a standard representation for clinical trial workflow diagrams in UML.

Methods

Two Brazilian clinical trial sites in rheumatology and oncology were examined to model their workflow and collect time-motion data. UML modeling was conducted in Eclipse, and a UML profile was developed to incorporate information used in discrete event simulation software.

Results

Ethnographic observation revealed bottlenecks in workflow: these included tasks requiring full commitment of CRCs, transferring notes from paper to computers, deviations from standard operating procedures, and conflicts between different IT systems. Time-motion analysis revealed that nurses'' activities took up the most time in the workflow and contained a high frequency of shorter duration activities. Administrative assistants performed more activities near the beginning and end of the workflow. Overall, clinical trial tasks had a greater frequency than clinic routines or other general activities.

Conclusions

This paper describes a method for modeling clinical trial workflow in UML and standardizing these workflow diagrams through a UML profile. In the increasingly global environment of clinical trials, the standardization of workflow modeling is a necessary precursor to conducting a comparative analysis of international clinical trials workflows.     

DataBiNS: a BioMoby-based data-mining workflow for biological pathways and non-synonymous SNPs

DataBiNS is a custom-designed BioMoby Web Service workflow that integrates non-synonymous coding single nucleotide polymorphisms (nsSNPs) data with structure/function and pathway data for the relevant protein. A KEGG Pathway Identifier representing a specific human biological pathway initializes the DataBiNS workflow. The workflow retrieves a list of publications, gene ontology annotations and nsSNP information for each gene involved in the biological pathway. Manual inspection of output data from several trial runs confirms that all expected information is appropriately retrieved by the workflow services. The use of an automated BioMoby workflow, rather than manual 'surfing', to retrieve the necessary data, significantly reduces the effort required for functional interpretation of SNP data, and thus encourages more speculative investigation. Moreover, the modular nature of the individual BioMoby Services enables fine-grained reusing of each service in other workflows, thus reducing the effort required to achieve similar investigations in the future. AVAILABILITY: The workflow is freely available as a Taverna SCUFL XML document at the iCAPTURE Centre web site, http://www.mrl.ubc.ca/who/who_bios_scott_tebbutt.shtml.     

Failure-aware workflow scheduling in cluster environments

The goal of workflow application scheduling is to achieve minimal makespan for each workflow. Scheduling workflow applications in high performance cluster environments is an NP-Complete problem, and becomes more complicated when potential resource failures are considered. While more research on failure prediction has been witnessed in recent years to improve system availability and reliability, very few of them attack the problem in the context of workflow application scheduling. In this paper, we study how a workflow scheduler benefits from failure prediction and propose FLAW, a failure-aware workflow scheduling algorithm. We propose two important definitions on accuracy, Application Oblivious Accuracy (AOA) and Application Aware Accuracy (AAA), from the perspectives of system and scheduling respectively, as we observe that the prediction accuracy defined conventionally imposes different performance implications on different applications and fails to measure how that improves scheduling effectiveness. The comprehensive evaluation results using real failure traces show that FLAW performs well with practically achievable prediction accuracy by reducing the average makespan, the loss time and the number of job rescheduling.     

A hybrid multi-objective metaheuristic optimization algorithm for scientific workflow scheduling

Cluster Computing - Workflow is composed of some interdependent tasks and workflow scheduling in the cloud environment that refers to sorting the workflow tasks on virtual machines on the cloud...     

流程化的生态建模方法与科学工作流系统

科学工作流系统是由一系列经过特殊设计的数据分析与管理步骤组成的、按照一定的逻辑组织在一起, 并在给定的运行环境下, 完成特定科学研究的工作流管理系统。科学工作流系统致力于使全世界的科学家可以在一个简单易用的平台上交换思想, 共同设计全球尺度的实验, 共享数据、实验步骤与结果等。每一个科学家可以独立创建自己的工作流, 执行工作流并实时查看结果; 不同科学家之间也可以方便地共享和复用这些工作流。本文以开普勒系统(Kepler system)和生物多样性虚拟实验室(BioVeL)两个项目为例, 介绍了科学工作流的发展历史、背景、现有项目和应用等。以生态位模型工作流为例, 介绍了科学工作流的流程以及特点等。并通过对现有科学工作流的分析, 对其发展方向和存在的问题提出了自己的看法及预期。     

Shotgun Mass Spectrometry Workflow Combining IEF and LC-MALDI-TOF/TOF

We present a high throughput shotgun mass spectrometry workflow using a bidimensional peptide fractionation procedure consisting of isoelectric focusing and RP-HPLC prior to mass spectrometric analysis, with the aim of optimizing peptide separation and protein identification. As part of the workflow we used the ‘Isotope-Coded Protein Labeling’ (ICPL) method for accurate relative quantitation of protein expression. Such workflow was successfully applied to a comparative proteome analysis of schizophrenia versus healthy control brain tissues and can be an alternative to proteome researches.     

Process-oriented ecological modeling approach and scientific workflow system

A scientific workflow system is designed specifically to organize, manage and execute a series of research steps, or a workflow, in a given runtime environment. The vision for scientific workflow systems is that the scientists around the world can collaborate on designing global-scaled experiments, sharing the data sets, experimental processes, and results on an easy-to-use platform. Each scientist can create and execute their own workflows and view results in real-time, and then subsequently share and reuse workflows among other scientists. Two case studies, using the Kepler system and BioVeL, are introduced in this paper. Ecological niche modeling process, which is a specialized form of scientific workflow system included in both Kepler system and BioVeL, was used to describe and discuss the features, developmental trends, and problems of scientific workflows.     

Improving the default data analysis workflow for large autoimmune biomarker discovery studies with ProtoArrays

Contemporary protein microarrays such as the ProtoArray® are used for autoimmune antibody screening studies to discover biomarker panels. For ProtoArray data analysis, the software Prospector and a default workflow are suggested by the manufacturer. While analyzing a large data set of a discovery study for diagnostic biomarkers of the Parkinson's disease (ParkCHIP), we have revealed the need for distinct improvements of the suggested workflow concerning raw data acquisition, normalization and preselection method availability, batch effects, feature selection, and feature validation. In this work, appropriate improvements of the default workflow are proposed. It is shown that completely automatic data acquisition as a batch, a re‐implementation of Prospector's pre‐selection method, multivariate or hybrid feature selection, and validation of the selected protein panel using an independent test set define in combination an improved workflow for large studies.     

Workflows in bioinformatics: meta-analysis and prototype implementation of a workflow generator

Background  

Computational methods for problem solving need to interleave information access and algorithm execution in a problem-specific workflow. The structures of these workflows are defined by a scaffold of syntactic, semantic and algebraic objects capable of representing them. Despite the proliferation of GUIs (Graphic User Interfaces) in bioinformatics, only some of them provide workflow capabilities; surprisingly, no meta-analysis of workflow operators and components in bioinformatics has been reported.     

A workflow management tool for laboratory medicine

To improve the efficiency and effectiveness of clinical laboratories, workflow analysis should be applied. To achieve this, specific laboratory functions and processes were identified. Methods for analyzing workflows and rules to control them are discussed. It is shown how workflow analysis can be applied in clinical laboratories using discrete event simulation. For this, a particular model (SCALES: Support and Consequences through Advanced Laboratory Expert Systems) is applied to analyze the workflow on several workstations. The results of a validation attempt are given. The information obtained from this study appeared to be very useful both from a methodological as well as a practical point of view.     

Response Surface Modelling for Performance Analysis of Scientific Workflow Application in Cloud

Scientific workflow applications are used by scientists to carry out research in various domains such as Physics, Chemistry, Astronomy etc. These applications require huge computational resources and currently cloud platform is used for efficiently running these applications. To improve the makespan and cost in workflow execution in cloud platform it requires to identify proper number of Virtual Machines (VM) and choose proper VM type. As cloud platform is dynamic, the available resources and the type of the resources are the two important factors on the cost and makespan of workflow execution. The primary objective of this work is to analyze the relationship among the cloud configuration parameters (Number of VM, Type of VM, VM configurations) for executing scientific workflow applications in cloud platform. In this work, to accurately analyze the influence of cloud platform resource configuration and scheduling polices a new predictive modelling using Box–Behnken design which is one of the modelling technique of Response Surface Methodology (RSM). It is used to build quadratic mathematical models that can be used to analyze relationships among input and output variables. Workflow cost and makespan models were built for real world scientific workflows using ANOVA and it was observed that the models fit well and can be useful in analyzing the performance of scientific workflow applications in cloud

     

Transparent mediation-based access to multiple yeast data sources using an ontology driven interface

Background

Over the past decade the workflow system paradigm has evolved as an efficient and user-friendly approach for developing complex bioinformatics applications. Two popular workflow systems that have gained acceptance by the bioinformatics community are Taverna and Galaxy. Each system has a large user-base and supports an ever-growing repository of application workflows. However, workflows developed for one system cannot be imported and executed easily on the other. The lack of interoperability is due to differences in the models of computation, workflow languages, and architectures of both systems. This lack of interoperability limits sharing of workflows between the user communities and leads to duplication of development efforts.

Results

In this paper, we present Tavaxy, a stand-alone system for creating and executing workflows based on using an extensible set of re-usable workflow patterns. Tavaxy offers a set of new features that simplify and enhance the development of sequence analysis applications: It allows the integration of existing Taverna and Galaxy workflows in a single environment, and supports the use of cloud computing capabilities. The integration of existing Taverna and Galaxy workflows is supported seamlessly at both run-time and design-time levels, based on the concepts of hierarchical workflows and workflow patterns. The use of cloud computing in Tavaxy is flexible, where the users can either instantiate the whole system on the cloud, or delegate the execution of certain sub-workflows to the cloud infrastructure.

Conclusions

Tavaxy reduces the workflow development cycle by introducing the use of workflow patterns to simplify workflow creation. It enables the re-use and integration of existing (sub-) workflows from Taverna and Galaxy, and allows the creation of hybrid workflows. Its additional features exploit recent advances in high performance cloud computing to cope with the increasing data size and complexity of analysis. The system can be accessed either through a cloud-enabled web-interface or downloaded and installed to run within the user's local environment. All resources related to Tavaxy are available at http://www.tavaxy.org.     

Topological analysis and interactive visualization of biological networks and protein structures

Computational analysis and interactive visualization of biological networks and protein structures are common tasks for gaining insight into biological processes. This protocol describes three workflows based on the NetworkAnalyzer and RINalyzer plug-ins for Cytoscape, a popular software platform for networks. NetworkAnalyzer has become a standard Cytoscape tool for comprehensive network topology analysis. In addition, RINalyzer provides methods for exploring residue interaction networks derived from protein structures. The first workflow uses NetworkAnalyzer to perform a topological analysis of biological networks. The second workflow applies RINalyzer to study protein structure and function and to compute network centrality measures. The third workflow combines NetworkAnalyzer and RINalyzer to compare residue networks. The full protocol can be completed in ～2 h.     

Integrating intracellular and extracellular proteomic profiling for in-depth investigations of cellular communication in a model of prostate cancer

Cellular communication is essential for cell-cell interactions, maintaining homeostasis and progression of certain disease states. While many studies examine extracellular proteins, the holistic extracellular proteome is often left uncaptured, leaving gaps in our understanding of how all extracellular proteins may impact communication and interaction. We used a cellular-based proteomics approach to more holistically profile both the intracellular and extracellular proteome of prostate cancer. Our workflow was generated in such a manner that multiple experimental conditions can be observed with the opportunity for high throughput integration. Additionally, this workflow is not limited to a proteomic aspect, as metabolomic and lipidomic studies can be integrated for a multi-omics workflow. Our analysis showed coverage of over 8000 proteins while also garnering insights into cellular communication in the context of prostate cancer development and progression. Identified proteins covered a variety of cellular processes and pathways, allowing for the investigation of multiple aspects into cellular biology. This workflow demonstrates advantages for integrating intra- and extracellular proteomic analyses as well as potential for multi-omics researchers. This approach possesses great value for future investigations into the systems biology aspects of disease development and progression.