►
Description
DevoWorm meeting: May 18, 2020. Attendees: Richard Gordon, Jesse Parent, Mayukh Deb, Bradly Alicea, and Susan Crawford-Young.
A
A
A
A
B
C
C
D
D
C
C
C
I
just
sent
me
a
gif.
I
don't
have
it
with
me
here,
but
it
was
just
like
a
basic
first
pass
approximation
at
it.
So
we
have
all
this
video
up
on
the
movement
database
that
basically
has
a
bunch
of
worms
that
have
been
observed
in
a
culture
and
they
are
moving
around
and
the
idea
is,
you
know,
you're
able
to
track
them
track
their
movement
using
different.
C
You
know
points
of
reference,
and
then
you
know
you
can
say
things
about
the
movements
you
know,
classify
them
and
so
forth,
so
he's
actually
using
a
machine
learning
approach
which
is
a
bit
different
from
what
other
people
have
been
doing,
and
so
you
know
we'll
see
where
that
goes.
It
looks
interesting.
There
might
even
be
some
applications
to
development
in
later
embryogenesis
when
you
start
seeing
muscle
twitching
in
the
worms,
for
example,
I
don't
know
if
we
can
get
video
of
that,
I
think
they
might
have.
C
There
might
be
some
data
sets
for
that
might
be
cleanly
captured,
but
we'll
have
to
look
around
for
that
and
anyways
I
mean
it
looks
interesting
so,
but
their
main
projects
are
not
starting,
yet
I
had
their
task
board
out.
I
don't
know
if
we're
gonna
get
to
that,
but
I
just
wanted
to
bring
that
up.
That's
what
we
were
gonna
hear
today,
but
I
should
ask
people
if
you
have
any
questions
or
comments
anything
we
should
catch
up
on
here.
D
D
E
C
C
C
So
we
have
a
bunch
of
things
that
have
already
been
completed
since
we
started
the
board.
A
couple
of
presentations:
google
summer
code
selections
the
virtual
worm
participation,
so
I
sent
out
a
link
a
couple
weeks
ago.
I
know
I
went
over
the
virtual
worm,
talk
which
was
well
received
and
I
sent
out
a
link.
C
C
I
think
it's
virtual
worm
lectures
or
something
on
youtube
and
it's
run
by
someone
who's
at.
I
think
baylor
college
of
medicine
and
they
wanted.
They
wanted
to
give
exposure
to
c
elegans
researchers
from
across
different
areas
of
c
elegans
research.
So
there
are
a
lot
of
good
talks
there
30
minute
talks
so
check
that
out.
If
you
can,
let's
see
oh
joao
was
also
going
to
present
on
cc
3d.
He
said
he
made
some
progress
on
the
so
the
cc
3d
is
the
copy
cell
3d.
C
Project
or
the
copy
cell
3d
program
that
he's
trying
to
build
models
in
so
so,
let's
see
what
we
have
in
progress.
We
have
this
axolotl
data
set
that
we
talked
about
it
several
weeks
back,
and
this
is
the
one
that
is
susan
from
our
group
here.
She
sent
me
some
data.
This
is
the
stuff
that
her
and
and
dick
have
been
working
on
with
the
flipping
microscope,
which
is
where
they
take
an
embryo
when
they
flip
it
and
they
image
the
sort
of
this
flipping
of
the.
C
So
it's
like
a
it's
a
ball,
so
it
rotates
around.
We
have
that
that
data
that
we're
trying
to
get
a
handle
on
it's.
You
know
it
really.
We
don't
have
a
good
path
forward
on
that
right
now,
but
we
have
the
data
and
it's
sort
of
sorted
and
ready
to
go.
So
we
need
to
maybe
work
on
that
a
little
bit
what
else
we
have
some
open
papers.
C
C
C
So
reason-
and
you
know
you
have
to
request
permissions
to
do
edit,
make
edits,
but
the
reason
I
do
it
this
way
is
because
you
know
people
want
to
contribute
to
something.
There
are
some
ongoing
papers
or
some
ongoing
ideas.
We
can.
Just
simply
you
know
someone
can
request
edit
access
and
maybe
make
some
contributions.
C
I
mean
you
know
the
it's
controlled,
so
it's
not
like
someone
random
person
on
the
internet
gets
in
there
and
makes
some
bad
edits
or
something.
But
you
know
it's
it's
yeah,
so
I
mean,
if
you're
interested
in
that
we
had
the
student
presentations
last
week
so
that
if
you
want
to
go
to
the
youtube
video
with
that,
it's
it's
there,
it's
just
the
two
student
presentations,
basically
their
proposals
that
they
had
or
it
could
have
been
two
weeks
ago-
well,
anyways.
C
And
we're
still
working
on
the
embryo
physics
archive.
That's
that's
up
on
on
github,
and
this
is
the
these
are
lectures
that
were
presented
probably
about
10
years
ago
now
in
that
area
of
time,
and
there
are
all
these
different
lectures
on
embryos
and
and
physics
of
development
and
so
been
re-archiving,
those
to
a
more
permanent
location
and
maybe
building
some
lesson
plans
around
that
or
some
curricula
around
that.
C
But
that's
something
also
that
you
might
want
to
you
know,
contribute
to,
and
then
that's
for
that's
pretty
much
what
we
have
in
progress.
We
have
a
couple
of
things
on
hold
the
divo
zebra
organization.
I
think
that'll
be
usually
project
the
axle
model
montaging,
which
has
to
do
with
the
axle
model
data.
C
I
think
that's
going
to
be
something
we'll
probably
need
to
plan
out
a
little
bit
more
in
terms
of
how
we
want
to
deal
with
the
axolotl
data.
I
think
the
idea
was,
I
think
I
sent
this
out
in
an
email
a
couple
weeks
ago.
It's
to
make
this
like
sort
of
google
map
of
the
embryo.
Where
you
have,
you
know,
you
have
the
surface
of
the
embryo
and
you
can
turn
it
and
you
can
see
the
surface
of
where
you
are
on
the
embryo
and
then
that's.
D
C
That's,
I
think,
that's
just
the
stuff
that
from
last
fall
so
this
this
is
just
the
version.
Well,
I
mean
I
put
that
up
on
on
google
classroom
so
that
people
could
have
it
all
in
one
place.
It
could
enroll
with
you
know
for
it,
but
it's
basically
all
this.
It's
basically
all
the
weeks
from
last
fall
that
we
did
that,
and
it
just
goes
through
different
topics
and
it's
kind
of
organized
weekly
by
topic.
So
people
can
view
that
and
that's
what
that
is.
C
Yeah,
so
this
is
like
this
was
the
idea
was
to
create
all
these
on
google
classroom
sort
of
is
like
a
skin
for
it
and
then
yeah
so
susan
and
you
can
just
ch
type
in
the
chat.
If
you
can't
get
your
sound
working,
oh
yeah,
we
were
talking
about
the
axolotl
data
and
sort
of
getting
a
plan
together.
For
that
I
am
waiting
for
some
people
to
you
know.
C
C
Maybe
yeah
may
26th,
that's
fine.
I
mean
that
we
have
enough.
I
think
we
have
enough
data
to
work
on
it
at
some
point,
but
yeah
we're
not
it's
not
like
at
the
top
of
our
queue.
But
if
we
find
someone
who
wants
to
work
on
it-
and
I
mean
we'll
probably
start
planning
it
out
and
it'll
be
you
know,
it'll
take
a
while
to
see
so
yeah.
So
that's,
okay,
so
I
was
going
through
the
task
board
susan.
C
So
I
think
you
can
see
my
screen
here,
so
I
was
going
through
this.
So
they
talked
about
the
axolotl
data
set
talked
about
the
papers
and
the
google
classroom,
which
includes
the
embryophysics
archive,
and
then,
let's
see
so
to
do.
There
are
a
bunch
of
thing
ideas
that
are
kind
of
fuzzy
here
that
we
were.
We
were
also
oh
right.
We
were
also
talking
about
the
embryo
visualization
for
docker,
so
I
don't
know
jesse
if
you
remember
that,
but
that
was
something
that
is
in
association
with
openworm.
C
C
That's
what
he
was
going
to
present
on
the
cc3d
stuff,
like
he's,
got
these
3d
models
that
he's
going
to
extrude
and
use
those
as
sort
of
I
don't
think
it's
supposed
to
be,
like
you
know,
a
high
resolution
model,
but
basically
like
something:
that's
just
a
demo
for
people,
because
we
don't
have
like
a
you
know,
a
lot
of
the
other
projects
and
open
worm
or
dedicated
software
projects
like
they're
doing
so.
It's
like
a
simulation
platform
or
something
so
they
have
like
this.
C
If
that's
what
you're
working
on
so
you
know
you
have
this
simulation
platform,
you
just
say:
okay,
build
a
simulation
and
spit
out
some
results
and
that's
the
whole
contribution
to
the
to
the
doctor
file.
But
this
is.
This
is
a
little
bit
different
because
we
don't
have
like
one
simulation
platform.
C
So
for
those
of
you
who
aren't
familiar
with
docker
docker
is
a
it's.
It's
like
a
sort
of
like
I
don't
know
if
you're
familiar
with
virtual
machines,
but
it's
something
you
can
open
up
on
your
computer
that
simulates
like
a
certain
set
of
operating
parameters.
So
the
benefit
of
that
is
that
if
you
send
this
docker
file
to
all
different
people,
you
know
with
all
different
types
of
computer
hardware.
C
C
C
C
C
So
yeah
I
mean
that's,
that's
what
we
have
so
we
have
like
basically,
four
things
that
are
really
kind
of
you
know,
I'm
sort
of
on
the
precipice
of
getting
done
the
rest
of
this
stuff
is.
It
needs
a
bit
more
work
to
really
stick
to
the
point
of
you
know
something
you
can
just
grab
onto
and
start
contributing
to.
C
C
C
Yeah,
don't
think
much
on
it.
It
was
just
something
we
kind
of
mentioned
in
passing
and
we
did,
I
think,
a
couple
of
paper.
We
looked
up
a
couple
papers
on
it
and
I
have
I
have
a
folder
in
my
hard
drive
and
it's
like
got
some
things
in
it.
I
thought
it
would
be
interesting
to
drive
forward
simply
because
it's
you
know,
that's
kind
of
the
thing
we
are
interested
in
here
is.
C
Yeah,
I
think
yeah,
I
think
it
like
you
know.
People
have
looked
at
like
looking
at
like
biocomplexity
and
looking
at,
like
you
know,
different
level,
different
sort
of
scales
of
an
organism
so
from
like
cells
to
genes.
To
you
know
the
whole
hierarchical
type
of
approach,
but,
like
you
know,
people
put
a
people
put
a
number
on
like
what's
the
complexity
of
an
organism
right
and
the
number
is
pretty
dependent
on
what
you
choose
to
measure.
C
So
you
know
the
the
idea
I
guess
would
be
you
know
we
maybe
would
propose
some
measures.
That
would
be.
You
know
good
for
sort
of
getting
a
better
understanding
of
biocomplexity
in
some
way
and
something
that's
robust.
I
know
people
have
done
this
in
the
past,
like
in
different
papers,
so
I
think,
there's
a
literature,
but
I
think
the
problem,
of
course,
has
always
been.
C
That's
a
pretty
like
you
know,
it's
a
pretty
abstract
thing
like
that.
You
know
they
have
things
like
scaling
laws
which
are
kind
of
like
where
they
put
a
bunch
of
organisms
on
a
chart.
They
say
this
is
body
size
and
it
scales
with
temperature
or
brain
size,
or
something
and
you
get
this
curve
and
it's
you
know
a
pretty
sort
of
vague.
C
You
know
measurement
it's
like
body
size,
they
measure
from
like
tip
to
tail
and
that's
supposed
to
tell
us
a
lot
about.
You
know
this
phenomena.
I
mean
it
scales
nicely,
but
what
does
it
really
tell
us
about
the
phenomenons?
Because
there's
you
know
the
it
isn't
just
like
this
length
measurement.
The
organism,
of
course,
is
a
three-dimensional
shape
and
then
you
know
it
moves
around
and
it
does
it
behaves
so
this.
This
idea
of
you
know
even
with
something
like
scaling
coefficients
and
scaling
laws.
C
So
I
mean
you
know
stuff
like
that,
where
it's
like
you
can
get
into
the
idea
of
like
you
know,
if
we
could
have
like
a
good
measure,
or
we
could
conceive
of
a
good
way
to
measure
biocomplexity
in
some
way
like
that,
you
know
we
might
be
able
to
derive
some
laws
or
some
sort
of
general
principles
about
how
this
unfolds
across
the
tree
of
life.
Because,
right
now
I
mean
we
have
like
scaling
laws.
C
We
might,
I
think
we
might
have
some
measures
of,
like
you
know,
complexity
like
with
circulatory
systems,
and
things
like
that
people
have
proposed
parameters
for
that.
But
I
don't
know
you
know,
I
don't
know
what
would
be
appropriate
there.
You
know
it's
something
to
think
about.
It's
probably
why
we
didn't
do
anything
with
it,
because
it's
such
a
broad
area
that
you
know
it's
hard
to
it
would
just
require,
like
you
know,
thinking
about
like
what
you
want
to
measure
and
then
maybe
we
can
use
some
real
data
to
measure
it.
C
C
C
So
yeah
just
take
a
look
at
those
links
and
then,
if
you're
interested,
if
if
it's
a
google
doc
request
access,
if
it's
a
good
repository,
you
can,
you
know,
fork
it
and
make
a
push
to
the
main
directory.
Or
you
know
just
you
know,
even
if
you
don't
feel
comfortable
in
github,
then
you
can
send
some.
C
C
C
C
C
C
One
main
criticism
is
that
the
background
algorithm
that
trains,
the
network,
it
doesn't
appear
to
have
a
biological
equivalent,
and
so
that's
one
thing
I
know
usually
esme
wrote
that
section
on
the
neural
network
descriptions
and
it
may
have
cut
out
some
relevant
detail
when
I
was
editing
it
for
the
first
round,
but
I
can
look
back.
I
think,
though
this
might
be
something
that
we
can
answer
pretty
quickly.
C
D
C
C
C
H
C
C
Let
me
know,
let
me
set
the
I'll
put
the
link
to
this
set
of
action
items
in
the
chat
here,
and
so,
if
you
need,
if
you
need
to
request
permissions
to
that,
do
so,
but
this
is
basically
our
our
action
item
list,
so
we're
gonna
try
to
get
this
done
the
next
couple
weeks.
I
think
we'll
just
have
to
follow
up
on
these
things
and
add
in
a
couple
of
new
references,
so
it
should
all
be
pretty
easy.
I
think
it'll
be
pretty
easy
to
do,
but
they've
ever.
E
E
C
That's
what
will
be
in
this
book
chapter
and
then
we
have
another
paper,
of
course
on
the
basil
area,
behavior,
and
so
that's
this
paper
here,
the
basilar
area
site.
Well,
I
have
his
paper
and
collective
pattern,
generators
which
is
the
bacillary-based
paper
and
then
the
bachelor
area
psychophysics.
So
we
have
two
sort
of
outlines,
and
then
these
are
in
the
google
doc
both
are
in
google
doc.
C
H
C
A
C
A
H
C
H
E
I
G
I
G
D
I
I
C
E
C
I
C
C
But
yeah
I
like
to
have
everyone
yeah
yeah,
but
yeah.
This
is,
I
think,
a
very
good
start,
but
I
think
we
have
you
know
it's
a
good.
It's
a
good!
Well,
first
of
all,
it's
a
good
practice
run
for
your
project,
but
also,
I
think,
there's
probably
something
that
should
be
done
with
just
general
motion
data.
D
C
So
I
mean
that's
what
they've
been
doing
in
the
movement
group
and
open,
except
they
haven't
used
machine
learning.
They've
been
using
mathematical,
modeling
I'll,
send
a
video,
a
recent
video
from
one
of
the
people
who
andre
brown,
who
works
in
open
room
on
the
movement
side,
and
he
they
have.
This
thing
called
terpsy
tracker
and
that's
their
sort
of
state
of
the
art,
and
he
gave
a
presentation.
I
Yeah
and
this
can
be
easily
fused
with
the
deepest
growth.
That's
the
objective
in
the
area,
safety
tracker
is
like
a
complete
product,
but
mine
is
like
a
product
which
can
be
plugged
into
a
deep
learning
model
so
that
it
can
scale
later
on
or
it
can
be
used
as
a
python
library
as
well.
By
the
end,
you
can
just
make
it
all
into
python
library.
This
can
be
used
to
track
and
do
anything
in
the
world.
C
I
F
C
C
F
C
C
C
Email
about
that
I
used
to
do
this
last
summer.
I
think,
and
then
I
stopped
doing
it
for
a
while
and
now
I
think,
it's
time
to
revitalize
it
a
bit,
especially
for
like
google
summer
code
people
if
they
want
to
talk
about
issues
that
they
have
it's
a
good
time
to
do
it.
But
you
know
that's
that's
separate
from
this
video
that
would
just
be.
D
C
We
have
so
many
things
going
on
in
the
group
that
if
you
want
to
catch
up
on
things,
you
know
we
have
another
time
to
do
it
well.
Thank
you,
mayor
for
your
update,
like
I
said
it
was
welcome
here,
yeah
and
we'll
be
doing
these
updates
every
week.
You
know
and
then,
like
the
coding
period
starts
in
live
weeks.
Also,
I
wanted
to
mention
you
know
we're
here,
but
we
have
this
this
wednesday.
A
C
C
C
C
C
H
D
C
D
C
C
C
C
D
C
C
C
C
C
C
There
are
a
lot
of
different
ways.
You
know
people
will
propose
different
models
for
how
striping
happens.
You
know
you
have
your
classic
model
like
your
turing
model
reaction,
diffusion
model,
but
there
are
other
things,
that's
alternative
to
it
as
well.
I
think
you
know.
Maybe
one
thing
we
can
do
is
give
a
presentation
on
at
some
point.
Someone
can
do
this
if
they're
interested
give
a
presentation
on
some
of
these
mechanisms-
and
you
know
kind
of
get
into
this
yeah
send
me
the
reference
or
the
vibration
work.
That'd
be
great.
C
We
can
maybe
present
it
here
or
we
can
at
least
make
people
aware
that
it's
available,
but
yeah
send
me
the
reference
and
but
yeah.
I
think
we
should.
We
should
follow
up
on
that
as
well.
If
people
are
interested,
definitely
a
lot
to
explore
in
that
area
as
well
is
like
machine
learning.
And
then
you
talk
a
lot
about
machine
learning,
but
you
know
agent-based
modeling
and
I
think
a
lot
of
these
cell
cell
models.
D
C
Interesting
in
their
own
right
because
they
give
us,
you
know
a
good
like
we're
talking
about
a
measurement
complexity
measures.
You
know
one
way
to
do
that
is
to
have
you
know
a
good
model,
a
sort
of
emergence
you
know
coming
from
like
say,
a
bunch
of
cells.
How
do
they
form
a
pattern,
or
you
know
even
like
how
gene
expression
contributes
to
cells
and
their
identity
and
their
patterns?
C
So
those
are
all
things
that
are.
You
know
interesting,
so
yeah
again
we'll
be
meeting
next
week.
This
is
we're
at
the
top
of
the
hour,
so
we'll
be
meeting
next
week
again
at
this
time,
we'll
be
getting
updates
and
we'll
try
to
do
like
10
minute
updates.
Okay,
just
be
prepared
for
the
feminine
synopsis,
and
then
you
know
we'll
discuss
it
a
little
bit
as
well.