
Ginkgo Bioworks (YC S14) raises $100M to buy a lot of synthetic DNA - johnsocs
http://techcrunch.com/2016/06/08/ginkgo-bioworks-grabs-100-million-in-financing-to-buy-a-whole-lot-of-synthetic-dna/
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jrkelly
I'm Jason Kelly, one of the Ginkgo co-founders -- happy to answer questions!

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hongloumeng
I'm a machine learning and have done work with Bayesian methods for modeling
dynamic systems. I've been considering jumping into a synthetic biology
company in industry. I've been searching for statistics and machine learning
problems that need solving in synthetic biology. I suspect that there are two
problems where a statistician or machine learning expert could contribute. The
first is building data-driven models of metabolic pathways. The second is
implementing an active learning approach to organism design -- basically
building a robot that iteratively conducts experiments that maximize
information while minimizing cost. But I also suspect that synthetic biology
companies like yourself and Zymergen are more concerned with scaling up your
business in the short term, and that implementing machine learning or
computational biology-types of processes is a long term "optimization" task,
not important to the core business in the near term. I'm afraid of making the
jump if this type of work isn't important to the organization. Can you please
comment? Cheers.

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overclocked
You mentioned two good examples of how a data scientist can contribute to a
synthetic biology company. Models are useful in many ways but only if they are
realistic and backed by data. Today, many models are limited in their
usefulness because they make assumptions to reduce complexity, assumptions
that are not always true in nature. We'd love to design iterative experiments
and gather more data, so we can improve and expand these models. However, to
end up with a useful outcome, we would need to a) test many designs and b)
capture as many experimental parameters as possible. We are working on (a) --
through increasing ability to synthesize DNA, and by improving our foundry
capability and scalability (so we can process and assay synthesized samples
and analyze results). (b) is extremely challenging due to the complexity of
biology. At Ginkgo, all data are analyzed by scientists and engineers with
high degree of biological intuition, so they can fill in gaps not captured in
data. For these reasons, we have focused our software and computation efforts
on building up wetware and automation infrastructure, so we can run more and
better experiments.

We are always looking for passionate engineers to join us to tackle tough
challenges. Just because something isn't doable today doesn't mean we can't
shoot for the moon! There's no better place to change how biology is
engineered than here. Ping us if you are interested in joining our efforts.

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vpontis
> The startup announced in the spring of 2015 it would be buying 100 million
> base pairs of DNA to help it move into new production areas but has since
> upped that amount to the 600 million base pairs and will be partnering with
> Twist Bioscience and Gen9 to supply the synthetic DNA. ____Twist has pledged
> to deliver at least 400 of those base pairs of DNA by the end of 2017. __ __

That last line about Twist delivering 400 base pairs has to be wrong, right?
Do they mean 400 million?

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jrkelly
Yes should be 400 million. 100 million from our last order plus 300 million in
this new order.

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vpontis
Ah great, that makes a lot of sense. Thanks for the quick reply!

How do you compare Gen9 and Twist? Do you use each for a specific type of
synthesis?

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sndean
> works with DARPA to produce probiotics that will help U.S. soldiers stave
> off stomach bugs

Will there be synthetic probiotics in the future? (I understand that some
probiotics are already heavily engineered.)

