Background: The development of high-throughput experimental technologies, such as next-generation sequencing, have led to new challenges for handling, analyzing and integrating the resulting large and diverse datasets. Bioinformatical analysis of these data commonly requires a number of mutually dependent steps applied to numerous samples for multiple conditions and replicates. To support these analyses, a number of workflow management systems (WMSs) have been developed to allow automated execution of corresponding analysis workflows. Major advantages of WMSs are the easy reproducibility of results as well as the reusability of workflows or their components. Results: In this article, we present Watchdog, a WMS for the automated analysis of ...
International audienceData analysis pipelines are now established as an effective means for specifyi...
Motivation: The rapid accumulation of both sequence and phenotype data generated by high-throughput ...
An in-silico experiment can be naturally specified as a workflow of activities implementing the data...
Background: The development of high-throughput experimental technologies, such as next-generation se...
Abstract Background The development of high-throughput experimental technologies, such as next-gener...
Information integration and workflow technologies for data analysis have always been major fields of...
Biological, clinical, and pharmacological research now often involves analyses of genomes, transcrip...
As the scale of biological data generation has increased, the bottleneck of research has shifted fro...
High-throughput technologies, such as next-generation sequencing, have turned molecular biology into...
Advances in sequencing techniques have led to exponential growth in biological data, demanding the d...
Background Reproducibility is one of the tenets of the scientific method. Scientific experiments oft...
Abstract The changing landscape of genomics research and clinical practice has created a need for co...
Information integration and workflow technologies for data analysis have always been major fields of...
Background Reproducibility is one of the tenets of the scientific method. Scientific experiments ...
International audienceData analysis pipelines are now established as an effective means for specifyi...
Motivation: The rapid accumulation of both sequence and phenotype data generated by high-throughput ...
An in-silico experiment can be naturally specified as a workflow of activities implementing the data...
Background: The development of high-throughput experimental technologies, such as next-generation se...
Abstract Background The development of high-throughput experimental technologies, such as next-gener...
Information integration and workflow technologies for data analysis have always been major fields of...
Biological, clinical, and pharmacological research now often involves analyses of genomes, transcrip...
As the scale of biological data generation has increased, the bottleneck of research has shifted fro...
High-throughput technologies, such as next-generation sequencing, have turned molecular biology into...
Advances in sequencing techniques have led to exponential growth in biological data, demanding the d...
Background Reproducibility is one of the tenets of the scientific method. Scientific experiments oft...
Abstract The changing landscape of genomics research and clinical practice has created a need for co...
Information integration and workflow technologies for data analysis have always been major fields of...
Background Reproducibility is one of the tenets of the scientific method. Scientific experiments ...
International audienceData analysis pipelines are now established as an effective means for specifyi...
Motivation: The rapid accumulation of both sequence and phenotype data generated by high-throughput ...
An in-silico experiment can be naturally specified as a workflow of activities implementing the data...