🧵🧵 THREAD: 9 tips for successful #bioinformatics #projects 🧵🧵
1. Start by defining the aim, scope, and objectives of your project, and by identifying the #biological and #computational questions you want to answer.
2. Identify the #data sources, types, and formats, that are relevant and available for your project, and evaluate their quality, quantity, and suitability.
3. Select the tools, methods, and #algorithms, that are appropriate and effective for your #project, and consider their performance, accuracy, and limitations.
4. Develop a clear and reproducible #workflow, that outlines the steps and tasks, and describes the data and tools, used in your project.
5. Use good software engineering practices, such as #version #control, #testing, and #documentation, to ensure the #reliability, #efficiency, and #maintainability of your code and results.
6. Use good data management practices, such as organization, #annotation, and provenance, to ensure the #security, #integrity, and #accessibility of your data and results.
7. Use good #computational #infrastructure, such as #cloud #computing, #containers, and #pipelines, to ensure the scalability, portability, and extensibility of your project.
8. Use always your scientific mindset, this will guide you through great hypothesis testing, experimentation, and reproducibility, to ensure the validity, robustness, and generalizability of your results.
9. project management: #planning, #monitoring, and reporting, to ensure the timely, efficient, and effective execution of your project.
Cloud genomics is a community of like-minded people looking forward to learn more about #Bioinformatics. Follow us for more information and support. #bioinformatics #computationalbiology #projectmanagement
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