[White Paper] Optimized Workflows in the Life Sciences

A bioinformatics pipeline is an analysis workflow that takes input data files in unprocessed raw form through a series of transformations to produce output data in a human-interpretable form.

A bioinformatics pipeline evolves through five phases. Pipeline bioinformaticians first seek to collect and explore the essential components, including raw data, tools, and  references (Conception Phase). Then, they automate the analysis steps and investigate pipeline results (Survival Phase). Once satisfied, they move on to seek reproducibility and robustness (Stability Phase), extensibility (Success Phase), and finally scalability (Significance Phase).

Where are you in the development of the optimized bioinformatics pipeline?

To learn more, download the "Optimized Workflows: Towards Reproducible, Extensible and Scalable Bioinformatics Pipelines" white paper brought to you by the Enthought Life Sciences Solutions Group, and explore:

• The five phases of bioinformatics pipelines and how to get to the next level
• The implications for labs in a competitive marketplace
• Real examples of challenges and solutions for each phase, related to: exploring protein reference databases, automating pipeline results visualization, improving a transcriptome analysis pipeline, transforming a metagenome pipelines framework, and handling memory exhaustion when scaling

Questions or want a consultation? Contact info@enthought.com to discuss how Enthought can help transform what’s possible in your R&D lab through optimizing workflows with machine learning and AI-assisted custom solutions.