Something that's been bugging me for a while in bioinformatics data analysis is this overreliance on packages, workflows and what's been called "cargo cult science".
Can we have more conceptual thinking, more theory?
Asking for what we really want to achieve and what we need to do gets us there.
Can we have more conceptual thinking, more theory?
Asking for what we really want to achieve and what we need to do gets us there.
Comments
In a way it's easier for discoverers. Once you discovered
something, it doesn't matter how you got there.
The keyword is "conceptual", taking a step back to see the forest for the trees; with or without mathematical models.
Do you have great examples of favorite "theory" papers from the last 1-2 years?
Where I think it has biggest impact is in mundane matters: being careful about units, sufficient vs necessary conditions,...
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That said, ...
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I think this happens in part due to a wish to pursue cutting edge tech (not necessarily a bad thing!), and w/more complex analytical methods there is a higher reliance on packages. I guess many researchers are blinded by this and forget *why* they are doing science in the process.
That's no contradiction to the original post (about good use of tools).
Biology is much more about historical contingencies than, say, physics or maths, and thus has more need for fact collections, "just so" stories.
Then people would need to actually think about designing new methods in their methods paper !
"I call these things Cargo Cult Science, because they follow all the apparent precepts and forms of scientific investigation, but they’re missing something essential, b/c the planes don’t land."
http://calteches.library.caltech.edu/51/2/CargoCult.htm
Now these *can* be useful. They're a great invention.
But many times I see people just show them because that's what people do,...
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Just think that these are necessary but not sufficient for doing science.
In those cases, people would really benefit from stating a more tangible goal, and see whether they actually get there.
“Why reinvent the wheel?”
Fair questions.
Ime reinventing often derives from theorycrafting, the need to adjust to real world data. Not all, ofc.
Therein lies the opposing force.
Re-use or re-invent?
But some understanding *is* required to use these tools, and without that it's easy to misuse them and even cause damage.
Some complexity and tradeoffs here, as so often.
For folks starting later on it's a standard "pipeline".
People avoid thinking, because it's easier and when copying what's published you don't have to justify your process.