Automation of in-silico data analysis processes through workflow management systems

Abstract

Data integration is needed in order to cope with the huge amounts of biological information now available and to perform data mining effectively. Current data integration systems have strict limitations, mainly due to the number of resources, their size and frequency of updates, their heterogeneity and distribution on the Internet. Integration must therefore be achieved by accessing network services through flexible and extensible data integration and analysis network tools. EXtensible Markup Language (XML), Web Services and Workflow Management Systems (WMS) can support the creation and deployment of such systems. Many XML languages and Web Services for bioinformatics have already been designed and implemented and some WMS have been proposed. In this article, we review a methodology for data integration in biomedical research that is based on these technologies. We also briefly describe some of the available WMS and discuss the current limitations of this methodology and the ways in which they can be overcome.

e-BioFlow: Improving Practical Use of Workflow Systems in Bioinformatics

“…Our experiences complement those of [2] and [4]. To demonstrate that many of the problems we found can be solved, we designed and built our own workflow system called e-BioFlow [9].…”

“…Today, workflow management systems (WfMSs) are recognised as useful tools for chaining computational tasks [1,2] and in particular for orchestrating web services [3,4]. Open-source WfMSs for scientific computation (e.g., Kepler [5] and Triana [6]) and specifically for bioinformatics (e.g., Taverna [7]) enjoy worldwide use.…”

Supporting NGS pipelines in the cloud

“…The availability of workflow management systems (Romano, 2007, Smedley et al, 2008 and public cloud computing infrastructures (Schatz et al, 2010) have become a major breakthrough in the usage of computing resources for scientists / the science community. However, the combination of both approaches has shortcomings (Magellan Final Report, 2011, such as the need to reduce administration effort to user, or the need for simple programming models for the transition from previous more conventional computing approaches and the support of legacy software.…”

Knowledge Based Expert Systems in Bioinformatics

“…More recently, semantic web based methods have been introduced that are designed to add meaning to the raw data by using formal descriptions of the concepts, terms, and relationships encoded within the data. Many of these technologies are reviewed in more detail in (Romano, 2008). Today's information-rich environment has also led to the growth of numerous software tools, designed to analyse and visualize the data.…”