
The most-cited papers - harleyk
http://www.nature.com/news/the-top-100-papers-1.16224?WT.ec_id=NATURE-20141030
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ebspelman
Really enjoyed the relationship between this paper's title and the graph of
its citation frequency:

[http://i.imgur.com/RO6BVRx.png](http://i.imgur.com/RO6BVRx.png)

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myth_buster
I think it would have been useful to have the graph reflect discipline's
color.

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adw
The Perdew-Burke-Enzerhof functional, and the generalized gradient
approximation, is a Big Honking Deal for accurate quantum-mechanical
simulation of solids.

For more:
[http://en.wikipedia.org/wiki/Density_functional_theory](http://en.wikipedia.org/wiki/Density_functional_theory)

(I used to be a happy customer, back when I was a scientist.)

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noname123
Flipped through to find whether genomics/bioinformatics would be well
represented; there were at least 2 papers on BLAST in the top 15, and 4th
paper is the Sanger method. But where is Watson & Crick?

My guess is that all of the subsequent papers that uses BLAST as a tool have
to cite it; similarly all sequencing papers cite Sanger as a tool which is why
its citation rate dropped when next-gen sequencing method replaced it - which
goes to show citation is not an accurate measure of scientific impact because
it is equivalent of citing "Git/compiler/IDE" for a software project.

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tedks
>which goes to show citation is not an accurate measure of scientific impact
because it is equivalent of citing "Git/compiler/IDE" for a software project.

The key difference is that BLAST is not a commodity, or at least was not at
the time of its release. If there was only one compiler, or one best compiler,
we would cite this in CS papers. In fact, "David A. Wheeler's sloccount" is
commonly cited in CS papers, as well as Weka, LLVM's Klee, and Z3.

On the other hand, nobody cites Djikstra's algorithm, or optimizing compilers,
because those are considered foundational and have not changed in a long time.
If BLAST was never supplanted, it would eventually not be cited because that
would simply be how sequencing was done. But since it represents a new
practice, citing it is necessary to place your work in the context of other
work.

I don't see how you can say that BLAST or Klee were not scientifically
impactful -- being the force multiplier that enables other avenues of research
is possibly the most valuable thing a scientist can do. For example, should a
paper that proves P!=NP become instantly the most cited paper in computer
science? Though the question is one of the most deep open problems in the
field, it isn't relevant at a lot of levels of study, and so it probably
wouldn't ever become more cited than Klee.

Further still, I'd guess that the top 1% of cited papers are mostly methods
papers, as the article bears out. The next tier are the top-notch findings
papers that you mention, because they spark other research. The C45 paper
probably doesn't have as much cites as Weka, because Weka is relevant beyond
C45, but it certainly has more cites than a less-meaningful machine learning
paper.

To carry all of this back to a software project, software projects in their
Readme.md always cite their language (like a key method), always cite their
dependent libraries (like specific methods used in that work), but never cite
things like binary search (a foundational finding). A project MIGHT cite a
compiler if that compiler is the only compiler that compiles it! In that case
the compiler is not a commodity, and thus worth citing. Version control and
editing are totally orthogonal to the actual software, unless you're working
in a visual language or something, in which case you would in fact cite your
IDE.

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noname123
Thanks for your detailed response. I see your point. Tangential, I used to use
Weka and liked it a lot and good to know that it is still very popular despite
all of the Big Data/Data Science touting Hadoop/Apache Spark.

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munificent
An interesting follow-up would be to run PageRank on the citation graph. That
should lower the importance of the scientific methods papers since they are
likely to be cited by a very large number of random papers of limited
importance, which bumping up papers that have led to further work that is
itself important.

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tokai
Citation count and co-authorship apparently does a better job at pointing out
good papers. Even though PageRank was in part inspired by citations studies.
[http://link.springer.com/article/10.1007%2Fs11192-007-1908-4](http://link.springer.com/article/10.1007%2Fs11192-007-1908-4)
(Paywalled)

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pcrh
Two of the top 10 are different editions of a laboratory manual: Sambrook, J.,
Fritsch, E. F. & Maniatis, T. Molecular Cloning (1989), and Maniatis, T.,
Fritsch, E. F. & Sambrook, J. Molecular Cloning: A Laboratory Manual (1982).

Citing Laemmli et al was _de rigueur_ for many years, while it was certainly
an influential technique, it doesn't rank above the discovery of DNA.

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z3t4
What I find interesting is that many papers use references from the 70's and
some times even 100 years old, in where they used very crude tools to come to
certain conclusions.

I'm not saying we should discard old science discoveries, but it would be
interesting redoing the experiments with today's technology.

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pcrh
Nobody discards "old" science discoveries, any more than they discard the
"old" inventions of steel, or indeed the wheel, they build upon them.

Re-visiting previous studies with newer approaches is a common theme in
archaeology, where sites or artifacts are sometimes incompletely investigated
on purpose, with the view to leaving undisturbed material that can be
investigated in the future using technology not yet conceived of.

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logicallee
I hope this doesn't make me sound like a hipster, but I can't remember the
last time I saw a wheel.

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JetSpiegel
How did you scroll this page?

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pedrosorio
Touchpad/touchscreen swipe?

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cal2
This is purely anecdotal, but one of my favorites is "Medical researcher
discovers integration, gets 75 citations."

[http://care.diabetesjournals.org/content/17/2/152.abstract](http://care.diabetesjournals.org/content/17/2/152.abstract)

