Notes from the life of a bioinformatician
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Subtitle: “Why some projects are not worth your valuable time and skills.”
Let’s wrap up this exploration of how to extract URLs associated with NAR Database articles. I’m tempted to start with the summary: don’t bother – just Google it. If you want that, skip to the end.
Read the rest…
Wikipedia defines factoid as “a questionable or spurious—unverified, incorrect, or fabricated—statement presented as a fact, but with no veracity.”
Last night I was enjoying a TV documentary series, The Story of Science, when I heard a startling factoid, namely:
If the “empty space” inside the atoms that make up people were removed, the entire human population would fit inside a sugar cube.
What the? Can we improve the veracity of this factoid?
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A recent question at BioStar asked “Is the NAR database list available in a computer readable format?” The short answer is “no” and Pierre has done some excellent preliminary work to address the issue.
I’ve been working on a database and web application to check the associated URLs but quite frankly, this is tedious, a waste of everyone’s time and could be entirely avoided if the publishing industry did a better job. All that’s required is that either NAR or PubMed provide structured data – XML, Medline format, I don’t care what – containing a field that looks something like this:
URL http://a.valid.url.goes.here
That way, we could all avoid writing regular expressions to detect URLs in abstracts. No wait – to detect broken URLs in abstracts. You would not believe how many of them look like this:
URL http://www.amaze.ulb. ac.be/
^
Someone helpfully informed me via Twitter that this is “often a result of typesetting.” Thanks for that.
If you:
just do this:
# at a shell prompt cp -r ~/R/i486-pc-linux-gnu-library/2.12 ~/R/i486-pc-linux-gnu-library/2.13 # in R console update.packages(checkBuilt=TRUE, ask=FALSE) # back to the shell rm -rf ~/R/i486-pc-linux-gnu-library/2.12
update: corrected a typo; of course you need “cp -r”
Once in a while, you embark on what looks like a simple computational procedure only to encounter frustration very early on. “I can’t even read my file into R!” you cry.
Step back, take a deep breath and take note of what the software is trying to tell you. Most times, you’ve just missed something very straightforward. Here’s an example.
Update: this post is not about how best to perform the task; it’s about how to cope with frustration. Please stop sending me your solutions :-)
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