
Successfully collaborating with computational biologists - azuajef
https://stactivist.com/2016/08/13/make-hay-while-the-sun-shines/
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JohnHammersley
Interestingly, some of the first interdisciplinary collaborations on
Overleaf[1] were between computational biologists (who tended to write up
their papers in LaTeX) working with non-computational biologists (who tended
to use Word), helped partly by the Rich Text mode we built[2] which hides
(most of) the LaTeX code for those who prefer to edit in a more WYSIWYG-style
environment.

We continue to see strong use in this area today, and indeed there seems to be
a growing trend for interdisciplinary collaborations (I'm one of the founders,
and we started it very much as a side project between mathematicians needing
to collaborate in LaTeX!).

It's also great to see that some of the newest innovations in publishing
platforms are in the (computational) life sciences area too, e.g.
F1000Research[3] (which offers open, post-publication peer review) and
PeerJ[4] (which has a membership model but no fee to publish).

[1] [https://www.overleaf.com/](https://www.overleaf.com/)

[2] [https://www.overleaf.com/blog/81](https://www.overleaf.com/blog/81)

[3] [http://f1000research.com/](http://f1000research.com/)

[4] [https://peerj.com/](https://peerj.com/)

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lukasLansky
What is the most impactful way one can contribute to the biological research
effort from distance as a programmer with some basic university-level
biological education? What open source project used in the area is both used
frequently and lacking in some important aspects?

I noted there were some bioinformatics project in the latest Summer of Code,
but they seemed to me more like "let's think how to teach our undergrads work
ethics" than "please, we really need this".

~~~
yread
These guys need all the help they can get

[https://summerofcode.withgoogle.com/organizations/5111396454...](https://summerofcode.withgoogle.com/organizations/5111396454891520/)

it's a Java backend with massive D3 frontend and import tools in Python. There
is a lot of issues at
[https://github.com/cBioPortal/cbioportal](https://github.com/cBioPortal/cbioportal)

And contributing is really smooth, the core developers reply fast and are
easy-going. Your github looks like you're interested in testing and that's one
area cbioportal is quite lacking. Might be worth a shot.

EDIT: Ozvi se, kdybys potreboval pomoc ;)

~~~
apathy
Galaxy could use the same.

~~~
jxtx
Contributions always welcome.

[https://github.com/galaxyproject/galaxy/labels/friendliness%...](https://github.com/galaxyproject/galaxy/labels/friendliness%2Fbeginner)

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astazangasta
I despise the computational/biologist split, where biologists know next to
nothing and can't even sort a spreadsheet. These days the bar to being a
"computational biologist" is super-low. (1) Can you login to a unix machine
and write a bash script? (2) Do you know what 'variance' is? You're good to
go! Because 99% of biologists don't know either of these things and don't care
to.

The number one thing that most biologists need (that most scientists need) is
a basic understanding of statistics when doing experimental design. Sure, you
can get this by having a computational biologist on staff, always timidly
raising their voice to get you to add replicates, for fuck's sake. But - how
about learning this stuff yourself, so your experiments (which rely deeply on
statistical reasoning) aren't shit to begin with?

My goal as a computational biologist isn't to do work for or correct
biologists who don't understand statistics, it's to get biologists tools to do
this kind of work easily on their own and bridge the gap in understanding. At
the end of the day, computational biologists can't have the important domain-
specific insights; biologists need to start understanding the datasets better
themselves so they can apply their domain knowledge to it, and computational
biologists need to be making tools to help them get there. Interdisciplinary
work succeeds best by constructing interdisciplinarians who have all of the
skills.

~~~
j7ake
I think making tools is a great thing to do as a computational biologist...
But I feel the main goal of a computational biologist is not to just make
tools but to make discoveries in ways that biologists could not have even
dreamed of. I hope one day this field of computational biology can stop
calling themselves computational biologists and simply call themselves
biologists.

I also find sometimes the inverse is true: computational biologists who don't
know any biology. I think there is work on both sides to bridge the gap.

~~~
ende
> I hope one day this field of computational biology can stop calling
> themselves computational biologists and simply call themselves biologists.

Absolutely.

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calinet6
Is there any collaboration for which these insightful realizations don't hold
true? This is great advice for the joining of any two fields or parts of a
process (in particular I'm thinking Design and Engineering are quite similar
in analogy).

