
Ask HN: Getting started in biology with a software background - nscalf
In the past few years the news around biology has been getting more exciting and frequent, between CRISPR and biotech firms working on niche drugs.  I&#x27;m really interested in learning more about the skills needed to start a biotech company, but I&#x27;m lacking the masters degree in biology.  What skills are actually needed to get into the field and does anyone know any good resources to learn them?
======
iongoatb
I'm curious who all these sarcastic bio "experts" are that are suggesting
getting a PhD or hiring one. I'm a former bio major and researcher/scientist
that transitioned to software engineering years ago. I've published papers in
bio and worked with many PhDs. Many of them were idiots. Being a PhD doesn't
mean anything, it's the independent work that you put in yourself (in an
academic lab or by yourself) that determines how skilled you become.

If you have strong CS skills then you should:

1) Focus on bioinformatics. You will immediately be of use as far as making
your own product/service or working for a startup if you apply your skills
there. Most bio specialists are incredibly weak at data analysis and/or any
type of computing. Pretty much all the important problems in bio are
computational in nature. The "impressive" bio researchers/scientists have the
data science skills of a sub-par / average data scientist / CS grad.

2) Create a home lab or find one / start one locally. Look up the odin
project. Work on DIY genetic engineering and you can even take classes from
that site. If you just get to this point and stop you will literally have more
practical skill and knowledge than the vast majority of graduates with bio
degrees.

3) Lots of biohackers experiment with themselves for clout/hype/attention. It
never ends well. There are plenty of lab organisms that you can easily source
and ethically experiment with.

4) Don't listen to anyone that tells you that you can't do something because
you don't have a PhD. Those are the same type of people that missed out on the
computing and internet revolutions because they were busy doing trivial
academic work.

~~~
Odenwaelder
1) Not enough for starting a biotech startup as OP would like to do. Having a
PhD means that you've spent years on a certain subject. You cannot just read a
book and be up to speed on biomedical research and CRISPR.

2) Having hands-on experience in wet labs is useful and relatively easy to
learn. People can learn wet lab skills sufficient to carry out experiments
(i.e. pipetting stuff together) in under a year. This is not what research is
about though.

3) True

4) You don't need a PhD. But to truly succeed in biology, you need to learn
things from the ground up, which takes years of studying. If you just read a
few books, you will be able to understand certain parts of it, but as a
founder of a biotech startup, you will be the equivalent of a tech startup
founder blindly following buzzwords such as "blockchain".

~~~
pkpkpk2
RE: "Having a PhD means that you've spent years on a certain subject. You
cannot just read a book and be up to speed on biomedical research and CRISPR."

Isn't that what books are for? To compile, document and share knowledge some
people spent years to figure out?

~~~
Odenwaelder
There is a huge gap between having knowledge from books and being able to do
original research, let alone solving a biomedical niche problem using CRISPR.
This gap is usually filled with an advanced degree, where you spend years in
the lab, keep track of the latest research in the field, try to find your
niche and solve the actual problem.

I mean, by all means, try it. But life sciences are not computer science. The
approach is entirely different and quality of the work you need to do is
different. It looks much, much easier than it is. (Which is, on a different
note, why I believe the whole pseudoscience crap such as anti-vaxxers is
gaining so much traction)

~~~
pvaldes
> But life sciences are not computer science

Exact

1) The use of materials is totally different

Computer programming is a stuf that uses reciclable electricity and "eating
your own dog food" kind programs, cheap to produce or free to copy, easily
available and in many cases free except by the hardware (Hardware that can be
hired, "clouded" or increased gradually).

You don't need to pay a dime for using R, C, Perl or Python and you can obtain
the four, ready to use in your computer in less than a half hour. If you need
a microscope, there is not an equivalent open source stuff replacement
available.

In Biology the matherials will be sold to you only in packages of 10 Kg each
pigment, with a caducity date, even when you would need to mix just 10 grams
of each one. The spendable one-use only stuff is not free and the price for a
single kit is incredible. You will pay it in any case because is indispensable
for validating your work and you plan to use 500 of those kits the next year
so you are a captive client from this company (that could decide to stop
selling you if you try a way to lower the price, and will sue you if you try
to copy the formula and make the product by yourself).

2) Documentation is not free and obtaining it is time consuming

In computer programming, you dont need to spent weeks to be delivered to you,
or plan a travel to Peru to collect samples of a plant virus. You don't need
to spend days just to reach the documentation navigating a miriad of closed or
pay per viewed journals, at 50 dollars to peek in each paper.

You can expect to learn something and use it for years. Fortran is still
there. You can program automatically your computer to make a hundred of safety
copies each working day. In biology you can not clone your amazonian beetles
collection, is unique and will be atacked and reduced to dust by real bugs
from day one if you do not protect it.

3) There is not an obvious, linear path to success

Errors are random events that you can't always control

In biology you will lose eight months of your research because your samples
travelling from Swedden to Madrid end somehow stuck in a Lithuanian airport
for ten days and now are defrozen and unusable. You needed this research to
assure the new funds and keep running, and now you have three months to obtain
new samples, redo and fix it.

You can lose years chasing a dead end or be superseeded by a genius in some
part of the planet that discovered the same as you first, or a different and
better way to do it.

4) You don't just buy a lab and hire a team to create "something" nice.

Unless you are in the bussiness of teaching science you design the lab
according of the exact product what you are trying to create. Any machine that
you ordered and will not use enough frequently later is a hole in your
presupuest. Any timed out kitt that you bought in excess quantity is your
money ending in the dumpster bin.

You need to hire somebody familiar with what "hardware" is trendy and works
and what machines are outdated since ten years even if you see it in each
faculty and in propaganda.

~~~
iongoatb
Describing the current state of CS and comparing it to the current state of
biotech/genetic engineering is like comparing apples to oranges. In the
beginning of the computer revolution the obstacles were extremely similar to
the current obstacles (or opportunities) with biotech. The materials were
expensive, documentation wasn't abundant, people didn't think personal
computers would ever be a thing or that people would interact on the internet
using social networks, and server/computing costs were extremely capital
intensive before cloud computing.

There is a great opportunity at this moment, similar to the opportunity that
Bill Gates and Paul Allen had. Mainframe computers were expensive, yet they
found ways to practice and become highly skilled. There wasn't documentation
like there is now, yet hacking culture found ways to build cool and effective
stuff. Obviously there wasn't a linear path to success - people thought
personal computers would never be necessary, yet Apple and Microsoft were huge
successes that no one ever expected. There are people that see opportunity in
fields like biotech and bioengineering, and there are people that only see the
obstacles. The former create amazing things, while years later the latter are
envious that they didn't have similar vision and courage.

You made my point.

~~~
pvaldes
>There is a great opportunity at this moment

I wouldn't advice to invest in the company of this guy, but is their money,
not mine, so... do as you please. Honestly, I would love to hear that he
became billionaire.

------
hprotagonist
Mostly, my advice as a biomedical researcher and modeler/software user is
this, which is not skills based at all and is instead just a reminder that
you're going to need a really fundamental shift in thinking.

Get the notion that "biology is a computer that we can fundamentally and
totally understand at the level that we understand Church-Turing" out of your
head as soon as possible because it is incorrect. Biological systems are
complex, they are deeply nonlinear, we do not even come close to understanding
the functional behavior of their components (or, indeed, what those components
even ARE) the way we can understand transistors or chips or API specs, etc.

The sooner you get used to believing that "I can't prove anything, but we have
a pile of mostly not contradictory evidence that suggests that most of the
time this idea is a pretty good heuristic and our error bars are reasonable",
the better you'll do and the saner you'll remain.

Some recommended worldview reading for you:

The Andy Grove Fallacy:
[http://blogs.sciencemag.org/pipeline/archives/2007/11/06/and...](http://blogs.sciencemag.org/pipeline/archives/2007/11/06/andy_grove_rich_famous_smart_and_wrong)

Can A Biologist Fix A Radio: [https://www.cell.com/cancer-
cell/pdf/S1535-6108(02)00133-2.p...](https://www.cell.com/cancer-
cell/pdf/S1535-6108\(02\)00133-2.pdf)

Can A Neuroscientist Understand A Microprocessor
[https://journals.plos.org/ploscompbiol/article?id=10.1371/jo...](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005268)

And if you like, I can provide a basically endless stream of papers of the
form "we thought X did Y and we knew what X was; it turns out that X actually
does Q, it also turns out we don't know why X does anything at all, but when
we do X we sometimes get Y so we've been confused for the past 50 years"

~~~
tikej
So much this. I think the most difficult thing about transition from hard
sciences such as cs/physics/math to wet science such as
biology/sociology/psychology is to get used to the fact that sometimes things
don't work and behave as expected and it takes enormous amount of work to get
it right.

Therefore you can't really go and design things form the first principles,
since first principles are not really that well known. Of course you can try,
and get some successes but that is rare. Add extremely complicated AND
nonlinear dependences between the systems you are working with and you may get
idea why we still don't have cure for most cancers yet.

~~~
perl4ever
"sometimes things don't work and behave as expected"

I think it's a great misconception to think that people who work with
computers work things out from first principles. Dealing with complex systems
that they don't understand, and repeatedly plunging into new areas, is exactly
why computer people think they can handle things like biology.

It also seems illogical to say "nobody understands biology, therefore you
cannot hope to". If nobody understands much, that makes it more likely an
outsider can contribute.

The attitude of many responses in this thread reminds me of the culture/class
gap I've seen between lawyers and legal IT analysts (one person I worked with
had a degree in biology as it happened).

~~~
tikej
By that I mean that in biology things are quite... Undeterministic. Working
with computer is (except some very rare cases) a work when non-deterministic
behaviour is most likely a bug. It's more or less the same in other hard
sciences.

In biology (and other non-hard sciences) the systems quite often behave in
non-deterministic way. To be clear I don't claim that this non-deterministic
behaviour is inherent to biological systems (although it is when we take the
quantum limit), but rather that they are so complex that untangling this
complexity to get nice casuality is virtually impossible. Add the complexity
and lack of understanding _on top of that_.

> It also seems illogical to say "nobody understands biology, therefore you
> cannot hope to".

I didn't mean to imply that "nobody understands biology, therefore you cannot
hope to". I rather meant to express that (at the current level of our species
and tools we have) "biology cannot be understood the same way computers are".
IMO of course. Therefore applying the same methodology that you apply to hard
sciences (math, phys, cs [, chem?]) may not yield as good results and often
doesn't.

> If nobody understands much, that makes it more likely an outsider can
> contribute.

I can agree that it's easier for outsider to contribute something to biology
than physics, mathematics or CS. However, to contribute meaningfully good
grasp of concepts and techniques is necessary. Contrarily to math, theoretical
or CS in biology it has to be acquired at the front lines of the battles i.e.
in the lab. I agree that bioinformatics has made huge leaps in the recent
years, but AFAIK nearly all significant new contributions in biology come from
the laboratory work not theoretical considerations.

------
shpongled
I'm in my 5th year of a chemical biology PhD and I'm looking to potentially
move into computer science/data science (been programming for 15 years) after
I graduate. Maybe we can just switch? I work with CRISPR for my project.

In all seriousness, you are going to need a PhD if you want to _truly_
understand all of the background of the field. Human biology/biochemistry is
just about the most complex thing humans have ever studied. It would surely be
easier to just find people with the requisite skill sets.

Even if you just want to start a company, I feel that it would be really hard
to pick out a scientific direction/what your company is going to do, without a
rigorous scientific background

~~~
codingdave
> you are going to need a PhD if you want to truly understand all of the
> background of the field

Is that the need, though? Few SaaS CEOs truly understand all the background of
computer science. They do understand the problem space, but they leave it to
the experts in the organization to get into the details of applying computer
science to the problem.

Is biology different, where the level of expertise needs to be at a more
detailed level in order to lead an organization?

~~~
shpongled
The key distinction here is starting a company vs leading a company. To just
walk in and lead an established company - you'd be fine with a better than
average understanding, as long as you trust the experts in your company to do
what is right.

To found a company? How do you know where to start? If you are hiring PhDs to
come up with the idea for you, how do you if their ideas are novel or
worthwhile?

Not to disparage SaaS founders, but I think it's somewhat easier to look about
and say "there is no app for sending texts via REST API" and do that, than it
is to look at say "no one has found a way to selectively target cancer cells
for CRISPR" and then go do that.

~~~
jayparth
I think the key distinction is that there is a well-established infrastructure
around software, such that the average SaaS founder (even 10 years ago) is/was
not doing fundamentally new things with computers. If they were, they would
probably need to understand computer science well. Take any moonshot ML
company- they need quite deep technical depth and usually have a founder that
has spent time in academia.

We are still at a point in Biotech where companies have to do fundamentally
new things with their tech to succeed. If you were starting a company that
applies CRISPR to X genetic disease, you might not need a Ph D. to start the
company, because you can apply existing technology to solve that problem. But
that begs the question: Why has no one else done it yet?

At the end of the day, you need a unique insight to start a large company.
That means experience with either the problem space or the technology space is
helpful. Not discouraging OP either, if you have a vision for what the future
should look like, and can acquire talent/capital... anyone can start a massive
company. So OP should try to acquire that vision.

~~~
Ultimatt
A big issue is its actually expensive to start a company that involves lab.
Software can genuinely be one person in their bedroom with some AWS credit. I
think the "why has no one else done this?" question is one of the worst anyone
in the history of business or science can ask themselves. Any opportunity
looks like that, it's why its an opportunity! The very best ones look like an
obvious gaping chasm when you see them.

~~~
jayparth
I'm in agreement with that sentiment. For any given opportunity, even if it's
"obvious" that someone should have done it, doesn't mean it's been done
before. If something seems like an opportunity you should probably try to
validate it, instead of immediately discounting it. That's how I started my
last company!

But there's no doubting that some sort of counter-intuitive or hidden insight
is necessary. Even if that insight is: "people think this is obvious and not
worth doing, but it actually IS worth doing." RE: Zero to One.

------
el_cujo
Your best bet is probably to look for a co-founder with an MS or PHD in
molecular biology rather than trying to get yourself to that level from the
ground up. If you have some biology background and just want to understand the
specifics of Crispr, you can start with this paper[0] and just google every
term you aren't familiar with until you make it all the way through. If you
don't know biology at all, this[1] is a common text book in undergrad programs
for molecular/cellular biology.

[0]
[https://www.ncbi.nlm.nih.gov/pubmed/23287718](https://www.ncbi.nlm.nih.gov/pubmed/23287718)

[1] [https://www.amazon.com/Molecular-Biology-Cell-Bruce-
Alberts/...](https://www.amazon.com/Molecular-Biology-Cell-Bruce-
Alberts/dp/0815341059)

------
rubidium
Go find a biotech company hiring software engineers where the biochemists are
in the same room/ building. Get a job there. Get to know biochemists and ask
them about their work and work problems, listen to their talks, read a lot.
Get mentored by a PhD in the field at the company.

When a new biotech product team is getting formed get yourself on the project.

Whatever you do, don’t compete with biologists.... there’s just too many of
them and the lab skills are valuable but in abundant supply.

------
baron_harkonnen
Right now I know a ridiculous amount of people with bio phds from top tier
schools that are trying to make it as data scientists. I don't think there is
a bio revolution like the software revolution that is happening quite yet.

I know quite a few bio/chem people working in pharma as well. That industry is
booming but mostly for the people that own pharmaceutical companies not their
employees. There's a reason that most biologists from good school would rather
be bad data scientist that good lab workers in pharma/bio tech. The pay is
much worse and pharma/bio tech don't treat there employees nearly as well as
big tech companies do.

All of the interesting jobs around that space are still largely tech jobs.

~~~
cryoshon
>I know quite a few bio/chem people working in pharma as well. That industry
is booming but mostly for the people that own pharmaceutical companies not
their employees. There's a reason that most biologists from good school would
rather be bad data scientist that good lab workers in pharma/bio tech. The pay
is much worse and pharma/bio tech don't treat there employees nearly as well
as big tech companies do.

yep, that's why i left the industry. the companies know that the science staff
are willing to work for less, so long as they have the opportunity to do what
they're interested in. so they end up working for much less.

------
cryoshon
my background is in biotech and i've worked at a small handful of biotech
startups in a scientific capacity.

here's my advice: unless you have friends who can set you up with the right
VCs and ensure that they will be willing to overlook your lack of experience
and IP, don't bother.

you're not going to get up to speed working in the lab on your own in any
short amount of time. learning the theoretical stuff that you need to know
won't take long, but you probably won't understand how to use the theory to
make something novel until you've spent time in the lab. and you won't know
how to vet the ideas of people with phds, either.

then there's the elephant in the room: risk. biotech is extremely risky
because drug development is difficult even under ideal conditions. making
"niche drugs" is even more difficult than making drugs for the mainstream
because niche diseases won't have as much of the scientific background already
researched when you sit down to try to come up with a useful therapy concept.

if you want to talk in more depth about the skills which are actually needed
to get into the field in a scientific or a business capacity, i've advised
someone who reached out to me here on HN about that exact topic in the past,
and i'm more than happy to discuss it with you via email. check out my profile
if you're interested.

~~~
unearthed
Why are Phds so cheap to hire if their skills are so valueable?

~~~
analog31
Disclaimer: I have a PhD. I think one problem is that the love of the subject
matter motivates people to go far beyond the bare minimum training required to
get a job.

~~~
perl4ever
Other comment mentioned game developers; I think another obvious comparison is
pilots. Anything people will do because it's fulfilling or prestigious or a
popular mission in life will produce an excessive number of applicants for
positions.

------
t_serpico
Biotech is a giant field, so it really depends what you want to do. I did my
undergrad in CS but spent the past ~4 years working at a molecular diagnostics
startup, where I do software engineering/stats/machine learning work. Along
the way, I learned a fair deal of biology, the fundamentals of the molecular
assays we work with, but more importantly the skills fundamental to science
(inquiry, designing experiments, generating new knowledge, skepticism, etc.).
Honestly, the biggest transition from CS -> sciences is not the specific
biology or understanding of experimental techniques, but rather learning how
to think like a scientist. These are skills you probably will not have if you
come from a strictly programming background.

If you are really serious about starting a biotech company, you will need to
get a PhD in an applied or natural science or work at an immature startup with
a team of PhDs thats needs programming help and you can hopefully learn the
'scientific' skills you need along the way. If you restrict the space of
companies you want to start to be strictly in the bioinformatics space, then
you can probably bypass the PhD route, but you'll need to get a job doing that
sort of work at a startup. Job descriptions for those roles should tell you
what specific skills you would need for that. Also, I would highly recommend
becoming good at stats. Thats fundamental to any path you go down, and can be
another way for you to provide immediate value to others.

------
pochekailov
I have spent 11 years in molecular biology research.

I must warn you about a survivorship bias. All the exciting news you are
hearing are the tip of a giant iceberg that rests on the mounts of a most dull
and repetitive labor.

Here are some realities that nobody tells you:

1\. There are only 3 operations done in experimental biology: liquid
pipetting, opening/closing tubes and moving tubes between machines. 90% of
protocols may be reduced to those operations.

2\. Just to reproduce an already published work, you need 6 month of 10
hour/day work, performing those 3 operations from point 1. It took 5 years to
reproduce just 18 molecular biology papers [[https://www.the-
scientist.com/news-opinion/effort-to-reprodu...](https://www.the-
scientist.com/news-opinion/effort-to-reproduce-cancer-studies-scales-down-
effort-to-18-papers-64593)], while 1 out of 4 computer science papers can be
reproduced in less than 30 minutes
[[http://reproducibility.cs.arizona.edu/](http://reproducibility.cs.arizona.edu/)].

3\. It takes days, if not weeks, to perform an experiment and make an
observation. That is, if you manage to make a mistake in your experiment at
day 2, you will only learn that something went wrong at day 6. Often, it is
even impossible to tell what went wrong.

3a. Imagine, that after days of coding, you hit "compile", and the compiler
would find a typo you made somewhere in your code, and instead of pointing at
the error, it would simply delete all your code, and never tell you what was
the reason, so you have to start over writing the code from scratch. This is
how day-to-day biology work looks like.

4\. CRISPR technology is one of the most heavy on 3 operations from point 1.

5\. If you ask biologists about how do they feel about doing experiments, 97
out of 100 will say they hate it the most and curse the day they decided to do
biology.

Regarding starting a company, I would first try to talk to as many as possible
industry people, trying to understand what they do day to day and what they
find most problematic, difficult or annoying to do, and see what you need to
do to solve their problem.

In fact, I so much hate the fact, that I spent 15 years studying, then 5 years
doing PhD, just so I can spent the rest of my days pipetting liquid. I decided
to try to automate away all manual work by creating a universal robotic
framework. If you are interested, please check
[https://cartesianrobotics.xyz/](https://cartesianrobotics.xyz/)

~~~
omar_a1
I was coming into this thread to recommend looking for entry level part time
mcb/bio lab work precisely because of point #1.

It's a wax on, wax off thing. The repetition gives you a chance to reflect on
the rationale for your technique and bigger picture of what you're doing, in
addition to getting hands-on experience in the field.

~~~
pochekailov
I think a part-time job would be an overkill

I have trained many students to do biology, and I can teach anybody, without
any education, to perform molecular biology experiments in 2 weeks.

I 2 months, they are usually able to generate scientifically valid ideas for
research (although, usually not the best ideas).

Biology is extremely simple as a field, and a computer scientist will have no
problem getting into the field (while opposite is usually hard)

~~~
omar_a1
I'd say there's no subtitute for hands on experience. In the same way people
on here recommend writing your own project to learn a language over simply
reading about it, actually doing lab work gives you an understanding that no
biology textbook can provide.

I vehemently disagree with the claim that biology is a simple field, and I'm
especially surprised to hear this from someone who did work in this field for
11 years. Anyone who has taken an intro biochem class would back me up on
this: life is complicated!

~~~
pochekailov
I completely agree about hands-on experience: yes, it is extremely useful to
practically do a biology engineering project. What I claim, is that about 2
weeks to 2 months of that is enough.

Regarding your second paragraph: I was fortunate to work in 3 fields in my
scientific career: organic chemistry, materials science/organic semiconductors
and molecular (synthetic) biology. This gave me ability to compare. What I
found out, is that biology has the most interesting problems nowadays, and
biology day-to-day work is extremely, outrageously, ridiculously stupid. I can
not even start describing how amazingly debilitating molecular biology methods
are. Right now, in the middle of the night I am stuck in the lab doing a day-
and-half long protocol, all consisting on steps like "put liquid in", "pipette
liquid out", "incubate for 5 minutes" and "shake for half hour".

Now here I am, after 15 years of school, 5 years of PhD and 11 years after
that, doing work which is less intellectual than flipping burgers in
McDonalds.

Fortunately, the fact that biology is so simple, gives me hope that it can be
automated fairly easily, which I am planning to concentrate on for the next 5
years.

Please don't mix the plain complexity of life, which appears like "too many
things to memorize", and complexity of mathematics and computer science, which
is "understanding deep layers of abstractions". While I haven't taken intro
bio classes, I read books and tons of papers. They are just plainly simple,
you don't need brain to read them, you only need to memorize.

~~~
kharak
Good luck with the robot. I wonder, if the individual steps are really that
simple, why hasn´t it already be automated already?

And if you don´t mind me asking, what´s the best way to start a little home
experiment to see if one may actually be interested in biotech?

~~~
pochekailov
Thanks! The reason it was not automated yet, is that non-biologists (including
CS engineers) don't know that individual steps are that simple; while
biologists do not have experience in thinking in abstractions, and so they
simply not seeing that they are doing effectively same operations, just with
different reagents.

In general, biologists are very busy pipetting faster than their peers, so
they can secure scarce professorship positions. They simply have no time
taking step back and looking at more general picture.

People who have skills necessary to build a robot and understand biology, have
opportunity to work for companies that pay salaries 5 times higher than
academia pays, so they don't bother.

I would not recommend doing any home experiments, especially without
professional laboratory experience. Most of the experiments contain dangerous,
poisonous or potentially explosive chemicals, and as for a newcomer, the risk
is too high.

Instead, I would recommend finding a local biotech interest group, join them
and go from there. Alternatively, you can find a local biotech lab and
volunteer to help a grad student or postdoc with their project. This is more
common than anyone may think. This way, there are no obligations, and you can
leave if you don't like it; at the same time, you will get exposure to the
state of the art biology.

Again, don't be afraid that you will not be able to bring anything good;
biology as a science is ridiculously simple, and if you already have CS or
electrical engineering background, you will have no trouble catching up within
a month or two (that is how long it takes to our grad students who come from
non-biology background to start bringing in new valid scientific ideas).

~~~
kharak
There are no wet lab communities out here (Switzerland), at least I couldn't
find any. But asking a postdoc to help out for free sounds promising.

Btw, I work 50 hours a week plus travel, I don't think it's going to be that
fast to get up to speed.

Cheers

------
tito
Check out Benchling! YC company (S12), founded by a CS undergrad from MIT. [1]
Learn more about their story. Biotech is growing so fast. There’s tons of room
for scientists and non-scientists alike. Programmers have a lot to add here,
even with zero bio background, the power of a fresh mind. Talk with scientists
and learn what problems they have.

[1] [https://www.crunchbase.com/person/sajith-
wickramasekara](https://www.crunchbase.com/person/sajith-wickramasekara)

------
xvilka
You certainly should check the Biostar Handbook[1] then and their forum[2].
BioJulia[3] is worth checking as well (I have really high hopes for Julia
language).

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

[2] [https://www.biostars.org/](https://www.biostars.org/)

[3] [https://biojulia.net/](https://biojulia.net/)

------
starpilot
Does this seem really incongruous to anyone else? It's like a biologist hears
something about Linux, and asks about how he can start writing kernel patches
having never coded anything in his life. It seems like there's an underlying
assumption that computer science >> all other sciences, as if the abstract
logic of computer programming is a substitute for basic domain knowledge in
other fields, often built over hundreds of years.

~~~
goatlover
You see this often when programmers comment on physics, neuroscience or even
philosophy. Everything is understood in terms of computer science and the
successes of the computer industry, because obviously reality is fundamentally
what programmers spend most of their time on. Which is something Jaron Lanier
pointed out a while back.

Of course I only mean some programmers, and I'm sure mathematicians and
physicists aren't immune to the same temptation. It's natural to understand
the world through the lens of what you understand best, but there are other
big fields of human knowledge out there.

~~~
sgillen
I think also they see that the gap between bootcamp grads or smart college
dropouts and a masters in CS is not necessarily that large, and assume the
same is true for other fields when that is pretty rarely the case.

------
jchallis
Join Lucence. Our dry lab and wet lab work are world class and you will learn
in the context of real problems for real patients with real samples.

We are hiring in SF and Singapore for informatics roles.

~~~
delinquentme
contact info?

~~~
jchallis
Email your CV and a paragraph on your interest to: hr at lucencedx.com

Bonus points for citing our active jobs page:
[https://www.lucencedx.com/careers/](https://www.lucencedx.com/careers/)

~~~
delinquentme
Generic HR inbox?

I don't think you're actually concerned about this.

------
teekert
I'm a self-taught bio-informatician (working at large healthcare company,
doing Next Generation Sequencing related things). although I am actively
seeking to better myself, My code is horrible, we have one "library" (a file
really) full of functions and since 2 months a couple of classes that I
already feel like completely re-writing. A lot of code is in Jupyter Notebooks
somewhere because we just got the hang of Git last year, let alone proper
branching. Pull requests? Yes I've heard of them. Transferring code to
partners is always troublesome. Man I wish we would have had a proper code-
writer on board from the very start, bonus points if that someone excited
about biology!

So bring it on I say! Just apply to any mayor classical bio-company. I mean
biologists need to become data-scientists and computer scientists more and
more, and they can use a lot of help. For example: During my internship in
2003 I did DNA sequencing, I spend all day making a gel and loading it and I
read 200 basepairs of DNA of a printed paper to check my results. Today we
have an Illumina sequencer in the lab, it produces 60 billion basepairs every
couple of days. We are nowhere anymore without computers and computer
scientists.

~~~
unearthed
I love git. Literally the only way to be productive when you've got more than
4 people touching code.

Do you guys allow remote work?

~~~
teekert
I work from home sometimes, and 1 of our team members is in the US (but still
at the same company). We have no people completely isolated that never come
into the office.

~~~
unearthed
I know for programmers / coders its a weird question but what about part time?

~~~
teekert
Why is this a weird question? I work 90% (36 hours) many of my colleagues work
32. In the Netherlands (in my bubble) it seems almost standard for both
parents to go to 32 (4x8) and both have one non-weekend day with the kid(s).

------
bbgm
There are two areas where you can jump in more easily with a CS/software
background. Many companies are building informatics/analysis pipelines. That’s
likely closer to what you know and you can pick up enough biology along the
way.

Alternatively there’s a lot of algorithm/classifier development you could jump
into.

It’s usually easier going the other way though. Biology is a complex beast.

~~~
bbgm
To be more specific, the first company I worked at had three co-founders; an
algorithms person, a functional biology expert, and someone with experience in
building software teams. The first two came from academia.

------
fabian2k
For most of the things you actually do in practice as a scientist in that
field you generally need to be trained by someone that knows the particular
area of biology and the specific methods you're using. It's not just about the
general background knowledge, which is certainly important, but on top of that
you need specific experience for each specialized area you work in.

Biology is a vast field, and there is simply an enormous amount to learn. And
you also need to understand the methods and techniques used to perform
experiments, which can get pretty deep into physics at times, and requires a
lot of very specialized knowledge for many of the more complex methods.
Statistics is also important for many types of experiments.

It's really not easy and fast to gain the necessary knowledge, people in the
field generally have a bachelor/master and a PhD, and that is the start of
your scientific career.

------
wonderwonder
Not mine but a useful link. Bioinformatics may not be exactly what you are
looking for but its a nice bridge between software and biology.

[https://github.com/ossu/bioinformatics](https://github.com/ossu/bioinformatics)

------
daemonk
I have a genetics phd and work as a bioinformatician. It takes time for
concepts to fully "sink in" in biology. Learning one independent
theory/fact/concept is great, but it is when you hook it up to all your other
knowledge that it becomes powerful. I would read as much as you can, wait a
month, then go back and re-read it. I promise you'll see and think about
things you haven't before.

The utility, in my opinion, of a phd is that you had 4+ years where you were
immersed in this environment and hopefully everything sunk in.

Biology is also not as black and white, cause and effect, strictly mechanistic
as CS/engineering. Always think about exceptions and grey areas.

------
esel2k
I lead projects with software and bioinformaticians in one of the worlds top
bioinfo/genetics company. If you want my opinion: Salary sucks in such
companies as there are way too many phds out there. Big egos and never built a
company... And bios have no clue about good engineering, TDD or CI. It is all
copy paste scripts.

So don’t compete with bio phds, the money is not worth it. I have studied
molec bio and comp science separately and can work in both industries. We talk
about 150k vs 100k salary differences. Find an area that interests you like
data analytics software in healthcare or something like this and go to a tech
company you will thank me.

------
WhompingWindows
If you're interested in genetic engineering/CRISPR, check out the following
book: Gene by Siddhartha Mukherjee. He does a fantastic job of layman's
writing on science, his other book on Cancer is fascinating and extremely well
written, that one is called "Emperor of Maladies". I'd highly recommend both,
but don't expect ANY other writing on bio to be that engaging :)

[https://www.amazon.com/Gene-Intimate-History-Siddhartha-
Mukh...](https://www.amazon.com/Gene-Intimate-History-Siddhartha-
Mukherjee/dp/1432837818)

------
iskander
I transitioned into cancer immunotherapy research after Computer Science grad
school. Biology is a mess and it will take several years to get up to speed on
any one research area. The best options are either grad school or finding a
job which doesn't initially require a lot of bio background but provides the
opportunity to learn. It's also worth checking out local biohacker spaces,
they can teach some basic techniques but you'll hit a ceiling quickly. To
really "start a biotech company" you'll really need to spend a long time
outside your comfort zone.

------
derekja
Where are you located? A lot of places now have community biology labs in
makerspaces that are doing really fun things. Start here:
[https://wiki.hackerspaces.org/Hackerspaces](https://wiki.hackerspaces.org/Hackerspaces)

Not all of the places on that list will have biology labs, but some will! It's
a good way to get some experience at the bench without going the degree route.

~~~
mindcrime
The hackerspaces.org link is good, but to add to that, here is a list that is
specifically "biohacker" groups/spaces.

[https://diybio.org/local/](https://diybio.org/local/)

For anybody in/near the Research Triangle Park area of NC, there is Tri-DIY-
Bio, a pretty active DIY bio group.
[http://www.tridiybio.org/](http://www.tridiybio.org/)

------
sxv
"Getting started in biology" and "starting a biotech company" to me are
opposite ends of a continuum, akin to "learning how to walk" vs "training for
a marathon". I made the transition from web dev to bioinformatics five years
ago and while I have a good job in academia, I wouldn't dream of starting a
bioX company without a bioX cofounder.

------
bioinformatics
I would start with genetics and genomics, then add some protein knowledge and
focus on the techniques that rely mostly on informatics/bioinformatics, like
Next-Generation Sequencing, chromatography and similar.

Add some evolution and phylogenetic, which with a mathematical background
should be straightforward to grasp.

------
strangattractor
The Bio tech seen is very credential focused. It is not like standard tech
that often welcomes people with other experience. There are several likely
reasons for this.

1\. An over abundance of Bio Phd's. 2\. Medicine in particular is tricky 3\.
Academics can be a$$Holes 4\. They don't pay as well.

------
pdm55
Zack Booth Simpson might be interesting to talk to:
[https://www.linkedin.com/in/zack-booth-
simpson-1084b3/](https://www.linkedin.com/in/zack-booth-simpson-1084b3/) He
transitioned from computers to biology.

------
dysoncdn
Learn biochemistry not biology

~~~
Ultimatt
Dunno the context of evolution goes a very long way even on the biochem.

------
ewewolfie
I find this resource very useful for learning bioinformatics:
[https://github.com/ossu/bioinformatics](https://github.com/ossu/bioinformatics)

------
RocketSyntax
Read "Genomics & Personalized Medicine; What Everyone Needs to Know"... twice,
paired w YouTube videos.

Work in the industry for a few years.

To be honest, the scientists just need big data + data science + workflows/
pipelines.

------
boltzmannbrain
Biotech startup school: [https://www.baybridgebio.com/biotech-startup-
school.html](https://www.baybridgebio.com/biotech-startup-school.html)

------
pfbtgom
You may way to look into biotech incubators such as IndioBio[1] to get an idea
of what it takes.

[1] [https://indiebio.co/](https://indiebio.co/)

------
pvaldes
> I'm interested in learning more about the skills needed to start a biotech
> company, but I'm lacking the masters degree in biology. What skills are
> actually needed to get into the field

You will need two basic skills

1) The skill to understand that trying to manipulate by yourself a delicate
and exquisitely calibrated machine without knowing what you do, is a bad idea.

There is a fair possibility that you end with either bad products like a
method for pursuing suspects based in DNA of a chunk of cut hair (made
entirely of cheratin that does not have any DNA). Incorrect biological
explanations or a very expensive machine broken are also probable results

2) The skill to hire a trained biologist that will do the job

------
freeradical13
I'm in a similar boat. I have a bachelors in computer science, 13 years in
industry, and I'm fascinated by biology.

The other comments are very good, so I'll add things I didn't see mentioned:

* In my opinion, you have to get beyond the wow factor and figure out _what_ you want to work on and _why_ , rather than the _how_ (e.g. CRISPR). I spent half a year researching this and my result was an interest in heart disease [1].

* Credentialism in biology is high, as mentioned. I'm currently in an M.S. in General Biology program. I was able to get my work to shift me to part time (20 hours/week) and I found a non-thesis M.S. program which is geared towards part time professionals (a rare program format) which is perfect for me. However, another comment mentioned biochemistry rather than general biology and there is some merit to that point, although I've appreciated the broader perspective of a general program.

* If you take the Biology credential path of M.S. or PhD, unless you go the Bioinformatics route, you'll likely need to take the GRE Biology specialty test, which was quite difficult for me with almost no biology background. It took me about 6 months to teach myself [2]. I liked the textbook "Campbell Biology" by Urry et al. as well as others, although I find the lack of citations in textbooks really annoying for the way I learn (following rabbit holes).

* Personally, I'm trying to avoid the bioinformatics route because I don't want to just be a tool of some other scientist, but I want to be a scientist myself. This is a hard path and there is some merit to others' comments about joining a biotech startup as a programmer and then transitioning to deeper biology.

* In my networking, I see a lot of people going the other way: from biology to computer/data science. Anecdotally, this seems to be largely due to points others raised: lower salary, a glut of PhDs, slow growth and conservatism of the field due to regulation, etc.

I don't know where I'll end up exactly, but I've thoroughly enjoyed the ride
and I think you should scratch your itch if you can. Feel free to email me
(email in profile) with questions.

[1]
[https://github.com/freeradical13/ValueBasedPrioritization/ra...](https://github.com/freeradical13/ValueBasedPrioritization/raw/master/value_based_prioritization.pdf)

[2] [https://freeradical13.github.io/](https://freeradical13.github.io/)

------
aaavl2821
I'm not a scientist but have worked in biotech in VC, started a venture backed
therapeutics company, and worked with the life sci group of a FAANG.

Having a PhD is not essential -- I know many successful VCs, founders and
operators without PhDs -- but you absolutely need an appreciation of science.
People like to hire PhDs because they have a fundamental knowledge of biology
and or chemistry and they have deep experimental experience in a specific
domain. Without that experience doing experiments it's hard to really
understand the challenges of science and rigor required. That said not all
PhDs give you that, and academic science tends to be less rigorous than
industry science

Also, developing a drug requires PhD level experience in many domains and no
one person can do it all. A neuroscience PhD won't necessarily qualify you to
review tox data. You need people who can quickly get up to speed on various
technical fields, find experts and have productive conversations with them

You need to understand the drug development process at a basic level. There
are lots of articles about this online, here's one I wrote [0]

You need to understand how to evaluate and critique scientific and clinical
data. It is easier to start by looking at clinical data. You can learn to
analyze this data without a PhD if you spend time with it and ideally have a
mentor. Here is a case study I wrote on basic concepts in evaluating clinical
data [1]

Evaluating preclinical or scientific data is much harder. In nonhuman studies
you are measuring more endpoints with less direct relationship to human
disease in more contrived systems. The experiments also tend to be less
rigorously designed, executed and documented (at least in academia) so there
are all kinds of pitfalls to avoid that you can't really know without
experience. This is where a PhD really helps

To start learning this just struggle through papers. Find a paper that
interests you and read it in depth. Learn what each experiment and instrument
does. Learn what each molecule does. Here's an example I wrote translating a
synthetic biology paper into layman studies terms to give you a sense of what
goes into reading a paper [2]

If you have a scientist friend who can walk you through papers that speeds up
the process by orders of magnitude and you can learn so much

At first read for comprehension. Then read with a critical eye. Why did they
do this experiment instead of this other one? Are they missing an important
control here? Is this model robust? Are the conclusions they draw stronger
that what the data suggest?

Learn how drugs are valued. Valuation is different in biotech than any other
sector. Drugs don't have revenue or users for years. A drug can. A worth $10B
before FDA approval. Value in biopharma comes from reducing technical risk. I
wrote a post about that here [3]. Most biotech founders lack either the
science or business knowledge needed. It is easier to learn the business stuff
so that can let you add value to a company while learning more about the
science

[0]
[https://www.baybridgebio.com/blog/drug_dev_process.html](https://www.baybridgebio.com/blog/drug_dev_process.html)

[1] [https://www.baybridgebio.com/blog/aducanumab-
analysis](https://www.baybridgebio.com/blog/aducanumab-analysis)

[2] [https://www.baybridgebio.com/blog/synbio-laymans-
terms.html](https://www.baybridgebio.com/blog/synbio-laymans-terms.html)

[3]
[https://www.baybridgebio.com/drug_valuation.html](https://www.baybridgebio.com/drug_valuation.html)

~~~
yowlingcat
I appreciate the plug to your blog -- subscribed! I really like your latest
post about Genentech. I never knew how related they were to Apple.

~~~
aaavl2821
Thanks! I didn't realize the connection until recently either. Bob Swanson is
a very underrated founder

