
Microbe computers - aethertap
http://stanmed.stanford.edu/2013fall/article10.html
======
logn
If we want bio computing to take off, somehow we need an IDE for this stuff. I
thought following install instructions for typical software was hard, check
this out:

[http://openwetware.org/wiki/ChIP-
Chip_E._coli](http://openwetware.org/wiki/ChIP-Chip_E._coli)

edit:

found this:
[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2989930/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2989930/)

 _BioCoder, a C++ library that enables biologists to express the exact steps
needed to execute a protocol. In addition to being suitable for automation,
BioCoder converts the code into a readable, English-language description for
use by biologists_

~~~
elsbree
Agreed, the current state of software tools for biology is sad- the tools are
written by scientists, for scientists, and tend to have messy source code and
incomplete/difficult to read documentation.

I don't mean to insult the people who work on the tools currently- they're
great! But we need more software people writing tools for the industry.

Fortunately, people are starting to do just that. TeselaGen and Genome
Compiler are both good examples. (Disclaimer- I'm a TeselaGen engineer)

~~~
Fomite
It's not necessarily a people problem as much as an incentives problem - the
incentives around Biology are, at present, entirely at odds with writing good
software.

Clean, well-documented source code won't get you grants. It won't yield
citations. It won't get you tenure. Beyond making sure you can run the same
code again, and it works if the postdoc who wrote it leaves, everything else
is under the "For the good of humanity" incentive structure. And with grant
paylines in the middling single digits, its really hard not to triage good
code in favor of making sure the lights stay on.

~~~
logn
That's interesting. I think if programmers in the biology realm open sourced
all their code, that might be incentive in itself to write good code. Once
multiple people start maintaining a project there's inherent incentive to have
nice code. In addition, there's a certain level of bragging rights of putting
an awesome project on your CV and getting future jobs because of that
codebase.

But it took years for your (now typical) OS, server, and Internet open source
projects to reach maturity and figure out how they can be monetized.

People in the sciences should start blogging more. People like me find all of
these subjects very interesting but very foreign. And I think many of us have
grown a bit bored with where most programming efforts are directed
(backoffice, ecommerce, and social apps).

~~~
Fomite
Three thoughts on this:

1\. Keep in mind for most projects and papers, not very many people are _ever_
going to use the source code. For most projects, there's almost no chance that
you're going to get a lively, multiple contributor project going. Odds are
it's just going to be on your shoulders.

2\. If you're going to stay in academia, there's no level of bragging rights
to an awesome project, and it won't particularly help your job prospects -
indeed from an opportunity cost perspective, most of the time it will hurt
them. Once the code is good enough for a paper to be written, the incentive to
do more work on the code vanishes.

3\. Science blogging is actually a pretty active field. But talking about the
software aspects of code don't get talked about as much because its just a
tool. There are some blogs on software for science drifting around out there
though.

------
lifeisstillgood
This feeds into one of my pet questions : will Moore's Law really die?

Doubling transistor density on silicon will end about 2020/22, when 7 or 5nm
etching occurs - beyond that and chip designers are past the wavelength of red
(?) light and into quantum tunnelling effects

But ...

 _maybe_ the amount of CPU cycles available to use for a given bi-annual price
will keep doubling. More efficient systems on a chip, cooling in huge data
centers means Siri can keep doubling its ability to run voice analysis on my
behalf?

is that true?

3\. is there genuinely any chance things like bio-computing?

~~~
wikiburner
Also:

Memristors

Graphene

3D Chips

Optical Computing

Spintronics

Quantum Computing

and I'm pretty sure I'm forgetting a couple of other promising paths to
extending Moore's Law.

Microbe computers strike me more as a path to nanorobotics.

------
jonmrodriguez
Hurray, Dr. Endy, Monica, Jerome, and Pakpoom! :) I interned in this lab and
it's really cool seeing their amazing work (especially using M13 for high-
bandwidth communication) get the press it deserves

Let's also not forget Paul Jaschke!
[http://www.researchgate.net/profile/Paul_Jaschke/](http://www.researchgate.net/profile/Paul_Jaschke/)
He was able to design and produce a working refactored version of the PhiX174
bacteriophage.

Refactoring in bio has the typical CS connotation of cleaning up messy code --
The natural PhiX174 has some overlapping genes that cannot be edited in
isolation -- The refactored version has no gene overlaps, so the genes can be
editted individually in a more rational manner.

------
mrcactu5
if the article is too difficult to follow, there is always

    
    
      Adventures in Synthetic Biology
    

[http://www.nature.com/nature/comics/syntheticbiologycomic/](http://www.nature.com/nature/comics/syntheticbiologycomic/)

That is the comic I read a Synthetic Biology REU at Princeton. At that point,
Drew Endy was at MIT and our leader Ron Weiss was at Princeton.

People have shuffled around a bit in 7 years
[http://openwetware.org/wiki/Endy:Lab](http://openwetware.org/wiki/Endy:Lab)
[http://groups.csail.mit.edu/synbio/](http://groups.csail.mit.edu/synbio/)

