The reproducibility of experiments has been a long standing impediment for further scientific
progress. Computational methods have been instrumental in drug discovery efforts owing to …

Background The complex nature of biological data has driven the development of
specialized software tools. Scientific workflow management systems simplify the assembly of …

A scientific workflow is a set of interdependent compute tasks orchestrating large scale data
analyses or in-silico experiments. Workflows often comprise thousands of tasks with …

Motivation A challenge for computational biologists is to make our analyses reproducible—
ie to rerun, combine, and share, with the assurance that equivalent runs will generate …

Computationally intensive disciplines such as computational biology often require use of a
variety of tools implemented in different scripting languages and analysis of large data sets …

The analysis of next-generation sequencing (NGS) data requires complex computational
workflows consisting of dozens of autonomously developed yet interdependent processing …

Universal search allows one to create an asymptotically optimal intelligent agent, which can
act in a wide range of computable environments. However combinatorial explosion is still …

Caches are essential to achieve high performance in modern hardware designs as they
bridge the performance gap between digital logic and memories. However, prior research …

Big data and complex analysis workflows (pipelines) are common issues in data driven
science such as bioinformatics. Large amounts of computational tools are available for data …

Scientific workflows provide a means to model, execute, and exchange the increasingly
complex analysis pipelines necessary for today's data-driven science. Over the last …