Authors:

Abigail Lin

Date Created:

Not specified

Course Title:

Professor:

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About Paper:

Computational methods are essential to modern biological research, yet many scientists face a steep learning curve with using the high- performance computing (HPC) required for large-scale data analysis. To bridge this gap, we have created user-friendly workflow templates that balance accessibility with scientific rigor. Our platform provides easy-to- use Console User Interfaces (CUIs) for key bioinformatics applications, including genome assembly, variant calling, and RNA sequencing. This allows researchers with little to no programming experience to execute complex analyses with ease, while also producing transparent and auditable code. Furthermore, we offer a general-purpose workflow template that enables users to construct custom bioinformatics pipelines, including automated CUI generation using configuration files. To ensure accessibility and reproducibility, all templates are accompanied by clear, step-by-step documentation that guides users through customization and deployment. By pairing intuitive interfaces and comprehensive documentation, our methodology lowers the entry barrier to computational research. It not only empowers a broader scientific community to harness HPC resources but also inherently promotes best practices of reproducible, scalable, and transparent science, fostering innovation and interdisciplinary collaboration. Keywords: Workflow; Bioinformatics; High-Performance Computing; Reproducibility; Pipeline

Source:

Purdue University / 2025

Topics:

No topics listed

Co-authors:

Abigail Lin