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Ten simple rules for defining a computational biology project
被引:0
|作者:
Noble, William Stafford
[1
,2
]
机构:
[1] Univ Washington, Dept Genome Sci, Seattle, WA 98195 USA
[2] Univ Washington, Paul G Allen Sch Comp Sci & Engn, Seattle, WA 98195 USA
关键词:
D O I:
10.1371/journal.pcbi.1010786
中图分类号:
Q5 [生物化学];
学科分类号:
071010 ;
081704 ;
摘要:
If you are working in the field of computational biology, then hopefully you are familiar with the excitement associated with coming up with a new idea and thinking about how to follow up on it. Maybe the idea came from a talk you heard at a conference, a paper you read, or a conversation with a colleague. Regardless, your brain is now abuzz with how this idea will be implemented and what data you'll need to validate it. Ultimately, if your idea pans out, perhaps it will lead to profound scientific insights, a high-impact paper, and a widely used software tool. But for now, it's just an idea in your head. How do you begin to bring your new idea to fruition? This is, of course, the core of the scientific method-transforming an idea (or hypothesis) into discoveries. Hence, your success as a scientist depends strongly on your ability to efficiently and effectively carry out such transformations. © 2023 William Stafford Noble. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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