Providing Map and GPS Assistance to Service Composition in Bioinformatics.

The wide use of Web services and scientific workflows has enabled bioinformaticians to reuse experimental resources and streamline data processing in a Web-scale manner. This paper presents a follow-up work of our network analysis on myExperiment, an online scientific workflow repository. The motivation comes from two common questions proposed by bio-scientists: 1) Given services which I plan to use, what are other services usually used together with them? and 2) Given two or more services I plan to use together, can I find an operation chain to connect them based on others' past usage? Aiming to provide a system-level GPS-like support to answer the two questions, we present ServiceMap, a network model established to study the best practice of service use. We propose two approaches over the ServiceMap: association rule mining and relation-aware, cross-workflow searching. Our approaches were validated using the real-life data obtained from the myExperiment repository. Empirical statistics of the constructed service network are also reported. © 2011 IEEE

ServiceMap: Providing Map and GPS Assistance to Service Composition in Bioinformatics.

The wide use of Web services and scientific workflows has enabled bioinformaticians to reuse experimental resources and streamline data processing. This paper presents a follow-up work of our network analysis on the myExperiment, an online scientific workflow repository. The motivation comes from two common questions raised by bio-scientists: 1) Given the services that I plan to use, are there other services usually used together with them? and 2) Given two or more services I plan to use together, is there an operation chain to connect them based on others' past usage? Aiming to provide a system-level GPS-like support to answer the two questions, we present ServiceMap, a network model established to study the best practice of service use. Two approaches are proposed over the ServiceMap: association rule mining and relation-aware, cross-workflow searching. Both approaches were validated using the real-life data obtained from the myExperiment repository. © 2011 IEEE

A comparison of using Taverna and BPEL in building scientific workflows: the case of caGrid.

When the emergence of 'service-oriented science,' the need arises to orchestrate multiple services to facilitate scientific investigation-that is, to create 'science workflows.' We present here our findings in providing a workflow solution for the caGrid service-based grid infrastructure. We choose BPEL and Taverna as candidates, and compare their usability in the lifecycle of a scientific workflow, including workflow composition, execution, and result analysis. Our experience shows that BPEL as an imperative language offers a comprehensive set of modeling primitives for workflows of all flavors; whereas Taverna offers a dataflow model and a more compact set of primitives that facilitates dataflow modeling and pipelined execution. We hope that this comparison study not only helps researchers to select a language or tool that meets their specific needs, but also offers some insight into how a workflow language and tool can fulfill the requirement of the scientific community. Copyright © 2009 John Wiley and Sons, Ltd

ServiceMap: Providing Map and GPS Assistance to Service Composition in Bioinformatics.

The wide use of Web services and scientific workflows has enabled bioinformaticians to reuse experimental resources and streamline data processing. This paper presents a follow-up work of our network analysis on the myExperiment, an online scientific workflow repository. The motivation comes from two common questions raised by bio-scientists: 1) Given the services that I plan to use, are there other services usually used together with them? and 2) Given two or more services I plan to use together, is there an operation chain to connect them based on others' past usage? Aiming to provide a system-level GPS-like support to answer the two questions, we present ServiceMap, a network model established to study the best practice of service use. Two approaches are proposed over the ServiceMap: association rule mining and relation-aware, cross-workflow searching. Both approaches were validated using the real-life data obtained from the myExperiment repository. © 2011 IEEE

Big Data:The challenge for small research groups in the era of cancer genomics

In the past decade, cancer research has seen an increasing trend towards high-throughput techniques and translational approaches. The increasing availability of assays that utilise smaller quantities of source material and produce higher volumes of data output have resulted in the necessity for data storage solutions beyond those previously used. Multifactorial data, both large in sample size and heterogeneous in context, needs to be integrated in a standardised, cost-effective and secure manner. This requires technical solutions and administrative support not normally financially accounted for in small- to moderate-sized research groups. In this review, we highlight the Big Data challenges faced by translational research groups in the precision medicine era; an era in which the genomes of over 75 000 patients will be sequenced by the National Health Service over the next 3 years to advance healthcare. In particular, we have looked at three main themes of data management in relation to cancer research, namely (1) cancer ontology management, (2) IT infrastructures that have been developed to support data management and (3) the unique ethical challenges introduced by utilising Big Data in research