

Ten Simple Rules for Starting a Company [PLoS Computational Biology] - michaelbarton
http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002439

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ahelwer
Does anyone have any advice for a computer science student seriously looking
at the field of computational biology as a place for a career? I'd all but
forgotten about biology until reading The Diamond Age right before seeing a
video of ATP synthase in action [1].

Now, I know stuff like that doesn't have a lot to do with what is done in
computational biology, but it did fire the imagination. I'm working my way
through Algorithms on Strings, Trees, and Sequences - Computer Science and
Computational Biology by Dan Gusfield [2], and have implemented (with tests)
all of the algorithms encountered thus far in addition to some of the
exercises [3]. So far, I really enjoy all the material.

Clearly reading a textbook is not enough to break into a field, but my degree
is one in computer science and pure math with an internship in the HPC field.
It's getting bit late to throw in a minor in biology or anything like that.
However, all of my research-leaning friends in physics and such tell me that
what everyone wants is someone who knows how to code, which is certainly
something I know well. Is that similar to the situation in computational
biology?

Any other advice or knowledge of what it's like to work in the field would
also be greatly appreciated :)

[1] <http://www.mrc-mbu.cam.ac.uk/node/448>

[2]
[http://books.google.ca/books/about/Algorithms_on_Strings_Tre...](http://books.google.ca/books/about/Algorithms_on_Strings_Trees_and_Sequence.html?id=Ofw5w1yuD8kC&redir_esc=y)

[3] <https://github.com/ahelwer/IvoryTower/tree/master/ASTS>

~~~
timr
It's pretty hard to give good advice without knowing if you want to go into
industry or academia. The job market for computational biologists in industry
is tight and problem-specific, and you'll generally need some research
experience before you can land a gig -- there's not much computational biology
going on that isn't considered "research" (even in industry).

That said, I'd recommend you start off by looking for a programmer gig in a
good research lab. It's not as difficult to get one of these jobs because good
CS students usually go into other fields, and academic labs are more willing
to train. Spend a few years there learning the process of research, and you'll
be much better qualified for an industry job. You'll also have a better idea
if you really want to pursue computational biology as a career.

Other posts in this thread recommend applying for engineering jobs at
biomedical startups (23andMe, Counsyl, etc.) That could be a decent option,
but remember: if you're working on the website (or the robots, or...), you're
not learning how to do computational biology. So it may not be the best long-
term choice if you're interested in the science. Make sure that the position
fits your long-term goals.

Finally, the general rule in computational biology is that "biology" is the
most important word. From the perspective of a biology researcher, programmers
are a commodity -- an expensive commodity, but still generic and
interchangeable -- but _biologists_ who know computer science are rare. The
only way to ensure long-term success in this field is to be the latter. So
regardless of what kind of job you pursue, make sure that you're spending at
least as much time learning the problem domain as you are learning about
computers. You really do need to become a domain expert. Being a computer
scientist isn't enough.

~~~
ahelwer
I would definitely want to go into industry. This is not to say I am averse to
getting a masters degree, but I am having great fun in my internship in the
private sector.

I believe I'll have one more summer left in my degree, so that's 4 months open
for an internship. Do you suppose it would be possible to get a meaningful
feel for the field in practice by finding an internship at a lab or company
somewhere?

~~~
timr
It's not much time, but it's better than nothing. You'll get a taste for the
field, but that's about it. Start looking now.

If you have another school year before graduation, you should also seriously
consider doing some work in a campus biology lab. If you're at a larger
school, there will be at least one lab that does computational biology work,
and if not...well, it's important to know something about biology. A winter
spent in a lab will be a learning experience, either way.

And if you're having trouble getting your foot in the door, here's an easy way
to get a gig in a campus lab: work for free. Tell them that you're a CS
student interested in computational biology, and that you'll be free, eager
labor if they'll let you learn about biology research. It's a time-honored
tradition -- nearly everyone in the field gets their start this way.

------
tdr
What a great reference!

Having already started a company, I can say this is true and wish this list
I'd had it before. BUT, the majority of these "commandments" I already knew.

The important point missing here is that until you do it on your own (solo or
with partners), you won't get that art & science part right: you'll just think
it's luck.

(prior expertise in your field + management/leading experience certainly
helps)

~~~
michaelbarton
Does the first point match your experience? I feel like VC emphasises getting
a great product ready first over everything else.

~~~
tdr
I agree with the point, although it's a little "all over the place".

I'm taking it as a "beware sign" for knowing what's ahead; i.e. to consider
the big-picture around whatever you are building (it's very easy to get sucked
into some "interesting direction" and get side-tracked; us geeks tend to do
that).

To answer your question: yes, if I would be an investor, I'd also want to see
the prototype/MVP, because:

\- less risk taken

\- 1 picture == 1000 words => demo == millions words

\- you show you can execute what you wish (not getting side-tracked)

from founder point of view because:

\- early adopters will help you shape your product (I just pivoted this month)

~~~
michaelbarton
I see what you mean about it being "all over the place" first they discuss a
great product alone is not enough but then instead talk about plans and ideas
rather than prototypes/implementations.

I've never started a business so my naive viewpoint is that many of the most
successful companies appear to be built on having a great product alone then
focusing on profit second, for example Google, Facebook, and Twitter. These
are the largest of the the large though, so is the story different for smaller
companies?

~~~
Estragon
Never started a company either, but I think the key issue is barrier to entry.
Facebook and Twitter have networks which are impossible to duplicate, and
Google got a lot of money up front and used it to move really fast. In
contrast, the great product they describe in the article is a standalone piece
of software by a small group, easily duplicated if it takes off.

