I am Eric Durand. I'm a computational
biologist here at 23andMe. I've been with the
company for about two years now. And I'm
mostly working on their ancestry products which range
from a variety of different problems. before that, I was a, a post doc at UC
Berkeley for another two years. And even before
that, I was a PHD student in France.
Well, so, a computational biologist, I think,
is always someone who's trying to develop
or at least to implement computational methods
to analyze biological data. So in, in my
field, in genetics. Even in my field, there is a wide variety of different data
and a wide variety of different applications.
So, a computational biologist could be someone developing
pipeline to analyze origin of sequences, for
example. Just from the raw data, to the
alignments, to culling the SNVs from the raw
data. And just process the data so it's
ready for statisticians for example, to try
to further process it. Could be someone like
me, who's, for me, a very bag, very big part of my job is machine learning.
So it could be someone who is
really interested in machine learning. And trying to
extract sense from the data directly. it comes
from the from the realization, I think, that
amount of genetic data is huge and growing
really fast. And even maybe more problematic is
the complexity of the data. Like any single
phenotype is going to be influenced by not
any single but many, many phenotypes is going to
be influenced by a lot of different genes. It's
very, very hard to find exactly the structure in
the data. So machine learning is one way to,
to tackle the problem. I and I think it's
a way that's proved successful already. So here at
23andMe, I think it's safe to say that all
the computational biologists came from the computer side of things.
They are of training either in computer science or in math or in
statistics. And they learn biology later as fascinating
application field for data scientists basically.
>> And so as you know, biology and genetics grows, you think there will
be a an opportunity for many more
computational individuals who are interested to sort of
learn genetics and biology and apply that.
>> Yes. Definitely. I think. I honestly think that biology is the
science of the 21st century, nothing less. And it will change everything
for most people. It will revolutionize
medicine being preventive or, or personalized.
It will, Yeah, it will basically change the daily life of, of everyone
I guess. And we need more people and I think many, many more jobs are
going to be created around, around in the computation of biology. So I
developed another features that 23andMe called ancestry
composition which goal is to find the origin of, of
segments. Not as precise as finding who you share
it with but where does it come from. So
it could come from some part of Europe. It could
come from some part of East Asia. Or some part
of Africa. so my undergrad was in applied math and
computer science. And then I went on to do a
PhD in Statistics. And because the way that was in
France and because the way it works in France, I
had to choose a field application for statistics. And that's,
only then, that I began to think about genetics. Because my PI was very
interested in population genetics, which is this field in genetics where we try
to learn about human evolution. So natural
selection, demography, ancestry, identity by descent. Then
I became interested as well, and I
developed statistical learning method to learn about
the, the genetic structure of such populations. After my PhD, I decided to do a
post doc here at UC Berkeley. Because I
had a very good opportunity with someone very
famous in the field of population genetics. And
there I was lucky enough to work on
the first draft of the neanderthal genome. So
I actually had the first full neanderthal genome
sitting on my hard-drive and I could just
do my, my stuff with it, anything I wanted.
>> That's awesome.
>> And I contributed to develop methods that, that
estimated amount of neanderthal DNA that modern humans have today.
>> if there was somebody watching this interview right now and
they're really intrigued about how biology and computer science and math,
statistics work together in, in a particular job, what advice
would you give them to, to study in school? What would
you recommend that they do, and maybe where would you recommend
that they seek you know, career advice or, or, or work
>> Yeah. so as I said, I do believe there is needs for
specialists or I do recommend they keep studying math and computer
science and statistics a lot. But they still need
to take some biology at the very least to figure
what are the problems that we need to solve
today in biology. And how to relate, you know it's
not enough to get out of school and know
a list of the ten fastest algorithms for each specific
problem that you learn in school. You also need
to be able to relate those great class of algorithms
to different problems in biology. How you will need to
adapt them, how sometimes you will have to realize that
there's nothing that exists already. And you need to develop
something that's not going to be optimal probably. But you need
to do a first pass of the problem. So you
do need to know enough biology at the very least
to understand the problems. Otherwise, for example, for ancestry, if
you don't have a very clear understanding of the recombination
process, there is nothing you can do. You need, you need to
understand exactly what probably stick model you can put in meiosis. How
often it's going to break a chromosome, all these things. So you, you,
you do need to know it enough biology to understand the problems.
>> Definitely.
>> So you need to take at least an
intro to biology class or something at the very least.