Michael E. Cotterell

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The wide-scale development of ontologies in the bioinformatics domain facilitates their use in the creation of scientific workflows. To speed up the design of workflows, a Service Suggestion Engine is interfaced to the Galaxy Tool Integration and Workflow Platform. This enables users to ask for suggestions (e.g., what operation should go next) while(More)
As recent programming languages provide improved conciseness and flexibility of syntax, the development of embedded or internal Domain-Specific Languages has increased. The field of Modeling and Simulation has had a long history of innovation in programming languages (e.g. Simula-67, GPSS). Much effort has gone into the development of Simulation Programming(More)
Predictive analytics in the big data era is taking on an ever increasingly important role. Issues related to choice on modeling technique, estimation procedure/algorithm and efficient execution can present significant challenges. For example, selection of appropriate/optimal models for big data analytics often requires careful investigation and considerable(More)
Predictive analytics and simulation modeling are two complementary disciplines that will increasingly be used together in the future. They share in common a focus on predicting how systems, existing or proposed, will function. The predictions may be values of quantifiable metrics or classification of outcomes. Both require collection of data to increase(More)
For a successful project development, it is important for any software organization that the project should be completed within time and budget, and the project should have requisite quality. This paper presents an Ensemble learning based Adaptive Neuro-Fuzzy Approach for Software Development Time Estimation. The concept behind this technique is based on(More)
Open Science Big Data is emerging as an important area of research and software development. Although there are several high quality frameworks for Big Data, additional capabilities are needed for Open Science Big Data. These include data provenance, citable reusable data, data sources providing links to research literature, relationships to other data and(More)
Predictive analytics in the big data era is taking on an ever increasingly important role. Issues related to choice on modeling technique, estimation procedure (or algorithm) and efficient execution can present significant challenges. For example, selection of appropriate and optimal models for big data analytics often requires careful investigation and(More)
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