SCIENTIFIC ACTIVITIES - Fields Institute - University of Toronto

Richard Cerezo: From my understanding
of the lecture, you characterized cell
motility by its activity with three proteins.
Leah Keshet: That was one aspect of a
bigger project in which the three proteins
play a major role, this is absolutely true.
When I give this lecture to biologists, I
tend not to do it quite in the same order…
Since I am giving the talk at the Fields
Institute I wanted to have a centerpiece
which was more mathematical.
RC: Are you a biologist or mathematician
by training, or both?
Siv Sivaloganathan: Her mother was a
pure mathematician and her father was a
biologist, so it was inevitable that she was…
LK: …stuck in between.
RC: I guess that comes across when you
have to tailor your talks to different
audiences.
LK: I try to, although you sometimes get
the opposite attitude and some people
say that to be in a field like this, you need
to be able to sit in two chairs, and you
need to have a very big bottom, because
biologists will say, ‘This is completely too
simplified’ and there is nothing biological
here. And mathematicians will come along
and say, ‘This is too soft, there is nothing
mathematically interesting here.’ So it’s
tricky.
SS: When you’re looking at a problem
that is essentially biological, how do
you go about thinking ‘what’s the crux
of the mathematical problem?’ How
do you go about formulating a problem
mathematically?
LK: Well it’s not trivial. It took many
years before we got to even asking the right
questions. We were stumped for a while
at the point where we saw, ‘these are the
three proteins, and these are the reactions.
We’ve simulated them but we don’t get
polarization. What’s going on here? Why
don’t we get what we want?’ To begin to
see what was happening took a long time.
To begin to formulate a simpler problem
that we could pursue analytically took even
more time. It’s been a total of seven or
eight years from when we began thinking
about these proteins.
SS: Would you say that apart from
experience, it’s a whole universe of things
outside the realm of mathematics that you
need to feel through to get a handle on the
problem?
LK: For the first five or six years, a lot
of the work is reading the literature and
figuring out what it means, rather than
having a biologist to work with directly.
This is because biologists rarely see the
value of models. The biologists who have
these values are rare and it takes a while for
us to build up enough of a background to
publish. I have collaborations with Condilis
in New York, which arose because I gave
a similar talk in Minnesota and he was one
of the people in the audience. He could
see that there was some value in those
directions.
RC: Was this approach to the problem out
of necessity or was this something that you
were trained during your PhD?
LK: I think it’s more a matter of luck.
That is, having the right people come
together at the right time. So when I began
thinking about this, I had a postdoc Stan
Moray [...] and he was a person who already
had these two dimensional simulations for
moving cell platforms—not so much as for
many cells interacting with each other, but
he could immediately see that this could be
done. While some students were working
out the biochemistry, we could then go to
them and say, ‘Here’s what we found,’ and
he could go then and make 2D simulations.
If we had to do everything from scratch, it
would have taken a long time.
RC: For the future generation of math
biologists, what attitude should we foster?
Since this is a highly non-traditional field
in mathematics.
LK: The good thing is that the field has
become more central and nowadays,
biologists typically have to show some
type of modelling component in their
grant proposals. They cannot simply
apply for NIH or NSF funding without
this balance. They have to show that they
have some way of taking that data from
their experiments and making sense of
it by working with theorists. Therefore,
they have much more motivation to be
connected to young people who’ve got
quantitative techniques. So I think it’s
important both to get the good math
background, which means PDEs, ODEs,
numerical simulation, a bit of computer
programming, knowing how to use
MATLAB, as well as taking the necessary
background courses in biology that you’re
interested in like immunology of cell
biology in my case, and then being very
open to talking to and finding people in
those fields to talk to.
SS: Because in many ways, biology up
until now has been just observation and
acquiring of lots of data. But trying to do
mathematics with objects that are not in
your chemical equations is something that
is just slowly sinking in.
RC: In what way, if any, did Professor
Lee Segal influence your work, your
approach, and your philosophy?
LK: Good question. I think first of all
that he was a great applied mathematician.
And I have to say that, despite all his
good intentions, he did not get me all
excited about asymptotic analysis. But
I did appreciate its usefulness, so other
people working with me deal with those
things. He had a way of taking problems
and saying, ‘How can we simplify this as a
first cut? How can we take something very
complicated and try and write down what
are the key things that we’ll go after as a
first version? Once we understand that,
we’ll add extra details.’ He was very good
at that.
[...] there are many scientists in every
area who are extremely possessive and have
the attitude of saying ‘this is my idea, this
is how it works’, ‘everybody else is a fool’,
‘this is the only way’. Segal was very much
willing to see all kinds of points of view and
debate, ‘well this kind of model can explain
this, the other kind of model is not so good
at explaining that’ and vice versa. He was
known in the field as being a great man,
almost a father figure, and I think that is
really important.
RC: So a human aspect was very
important, as well as his ability to relate
to other people, not only his ability to be
solely a scientist?
LK: To bridge between different
perspectives and not be too put off if
someone thought that ‘no actually, things
work a different way’, to be tolerant of
different points of view and be open.
SS: This is interesting because we
had a workshop a couple of weeks ago
on Mathematical Oncology and one
of the students of Weinberg at MIT
was speaking and I was talking to him
afterwards and he was saying how he got
to work with Weinberg. Weinberg said to
him ‘anybody could be a great scientist, I
want you to be a great human being’ and I
thought that was a wonderful thing to say.
FIELDS INSTITUTE Research in Mathematical Sciences | FIELDSNOTES 19