Design of reproducible computational pipelines for biological data processing and analysis.
Pipelines can combine preprocessing, quality control, analysis tools, machine learning models, databases, workflow management, and reporting.
They can support genomic, transcriptomic, protein, ecological, and other computational biology workflows.
Implementation is selected according to the available data, technical constraints, required level of automation, and the existing software or research environment. The solution can be implemented as a standalone component or integrated into a larger system.
The resulting system is intended to provide a clear computational workflow that can be evaluated, maintained, and extended as the project develops. Model choice, data processing, interfaces, and deployment can therefore be adapted to the requirements of the specific project.