Scientific research relies as much on the dissemination and exchange of data sets as on the publication of conclusions. Accurately tracking the lineage (origin and subsequent processing history) of scientific data sets is thus imperative for the complete documentation of scientific work

that can conceptualize the different effects of rewards on behavior. The scientific investigation of behavioral processes by animal learning theory and economic utility theory has produced a theoretical framework that can help to elucidate the neural correlates for reward functions in learning, goal

The bioinformatics scientific process relies on in silico experiments, which are experiments executed in full in a computational environment. Scientists wish to encode the designs of these experiments as workflows because they provide minimal, declarative descriptions of the designs, overcoming

associated with data origins, whereas traceability concerns the interlinking and exe-cution of processes. This paper proposes a set of mech-anisms to deal with this last aspect, the solution is based on database research combined with scientific work-flows, plus domain-specific knowledge stored in ontol

Motivation: Crystallographers were motivated 10 years ago to develop a simple and consistent data representation for the exchange and archiving of data associated with the crystallographic experiment and the final structure. As this process evolved (and the data grew at near exponential rates) came

Background: Predicting protein function has become increasingly demanding in the era of next generation sequencing technology. The task to assign a curator-reviewed function to every single sequence is impracticable. Bioinformatics tools, easy to use and able to provide automatic and reliable

of biological data. This data can consist of the information stored in the genetic code, and also experimental results (and hence imprecision) from various sources, patient statistics, and scientific literature. Bioinformatics combines computer science, biology, physical and chemical principles, and tools

Summary: Bioinformatics is a new scientific discipline, connecting together technology and biology. Large amounts of data coming from organism’s micro-level can’t be processed without computer’s support. Nowadays many bioinformatics tools are internet-available. Using these resources for practical

discovery, workflow enactment & distributed query processing. Additional services are provided to support the scientific method & best practice found at the bench but often neglected at the workstation, notably provenance management, change notification & personalisation. Results: We give

of workflows between the two platforms. This enables a convenient development, debugging, and maintenance of scientific workflows on the desktop. These workflows can then be deployed on a cloud or grid, thus permitting large-scale computation. To achieve our goals, we relied on a Common Tool Description XML