►
From YouTube: DevoWorm (2020, Meeting 19): GSoC project updates, issues review, developmental bio papers.
Description
Attendees: Bradly Alicea, Susan Crawford-Young, Mayukh Deb, Steve McGrew, Ujjwal Singh, Richard Gordon, and Vinay Varma.
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I
mean
cells
have
sort
of
an
irregular
surface
to
because
you
have
a
lot
of
receptors
and
things,
but
that's
I
mean
that
the
fact
that
you
can
make
that
sort
of
surface
you
know
it
doesn't
have
to
be
smooth.
This
is
interesting
in
the
single
cell,
so
that's
good
I
mean
again
we're
gonna,
be
you
know,
probably
revisiting
this
a
lot
so
but
that's
I
think
that's
good
progress.
E
F
C
G
F
E
C
C
D
C
G
E
C
C
C
C
This
is
this
is
the
blog
post,
so
this
is
so
week
three.
This
is
we're
talking
about
the
skeletonization
process
and
then
student
rhetoric
turn
towards
data
analysis,
which
I
mean
it's
probably
going
to
because
you're
getting
data.
Now
you
want
to
explore
it,
so
you've
got
the
videos
from
the
movement
database
and
you're
just,
and
so
this
is
the
time
series,
and
so
you
give
me
that
you've
got
a
wild
type,
which
is
the
n2
worm
and
a
nun
commute
which
is
like
one
of
the
defined
mutants
that
they
have
for
C
elegans.
C
So
C
elegans,
of
course,
has
a
lot
of
defined
mutants.
We
know
defined
mutant,
meaning
that
we
know
that
every
worm
in
that
string
carries
a
mutation
in
a
certain
gene
and
so
the
uncommunicative
a
certain
mutation
in
an
umpteenth
that
they
define.
Then
they
have
more
definition
in
their
metadata
for
the
video.
But
for
our
purposes
you
know
we're
just
saying
it's
beautiful,
I'll
type
and
then
yeah.
We
get
a
lot
of
difference
in
terms
of
the
movement
patterns
or
in
terms
of
this
time
series.
C
So
you
know
in
some
of
the
meters
there
perfectly
weren't
they're
perfectly
normal
locomotion,
but
another
mutants
such
as
this
one.
You
see
differences
in
in
the
pattern
and
they're
pretty
stereotyped
patterns,
so
we
should
expect
you
know
pretty
good
correspondence
between
worms.
This
time
series
at
least
they
faked
I,
don't
know,
I,
don't
know
what
kind
of
data
they
have.
It
might
be
worth,
maybe
taking
another
while
another,
a
couple
of
different
types
of.
C
E
C
C
Then,
let's
see
it
is
possible
to
generate
a
large
amount
of
time
series
data
from
the
videos
that
are
available
on
the
database
time
series
can
use
for
two
possible
purposes.
First
would
be
is
would
be
to
use
an
LST
m
to
predict.
The
future
sequence
of
values
would
be
able
to
find
an
underlying
pattern.
D
F
F
D
G
D
D
C
Good
and
then
another
possibility
to
be
to
use
the
LS
TM
to
classify
the
worms
string
based
on
the
time
series
data,
that's
quite
like
identifying
things
by
their
signature
basically
mean
that
would
be
useful,
probably
for
like
maybe
for
developmental
data
as
well
as
for
movement
data.
Just
you
have
a
landmark
in
the
series
of
images
you
can
track
its
presence.
G
C
Might
put
them
may
also
be
useful
for
a
lot
of
other
things
too.
So
I
think
that's
a
nice
general
type
of
approach,
and
so
this
is
a
simple
LS,
TM,
r
and
n,
which
is
a
recurrent
neural
network.
When
the
time
series
data
is
a
premium
concept.
So
this
is
what
the
predictions
are.
This
orange
line
here.
C
C
So
now
you
have
the
coding
period
that
you're
gonna
enter
into,
and
so
this
is
gonna
be
period
where
you're
gonna.
You
have
your
proposals
that
you
wrote
and
now
you're
gonna
be
going
through
there.
Your
schedule
on
the
proposals,
and
so
this
is
much
more
sticking
to
the
well.
You
don't
have
to
stick
to
the
proposal
directly,
but
this
is
where
you're
going
to
be
working
on
what
you
had
the
deliverables
as
you
had
outlined
in
your
proposal
so
but
I
want.
You
know,
I
want
you.
C
If
you
can
to
keep
working
on
this
a
little
bit
and
see
where
it
goes
I,
you
know,
I
think
it's
promising,
but
I
also
want
to
make
sure
that
we
have
like
we
understand
that.
There's
like
we
have
to
work
on
the
deliverables
that
we
have
in
the
proposal
that
we
had
originally
set
forth
now
in
terms
of
like,
if
you
have
problems
this
summer
with-
and
this
happens
all
the
time
this
isn't
just
like
because
of
the
summer
is
weird
because
of
the
pandemic,
you
can
modify
or
Reese
cope.
Your
proposal,
timing.
F
C
If
you
have
problems,
tell
me
or
tell
the
group
via
the
transparent,
about
your
problems,
if
you're
having
like
a
problem
with
something
running
or
something,
let
us
know
that's
why
we
do
the
weekly
updates,
then
the
other
is,
we
will
go
through,
I
think
a
regular
intervals,
maybe
every
couple
weeks
and
reassess
the
timeline
so
I
have
you
know
we
I
give
you
some
I,
have
a
couple
of
reviews.
I
have
to
submit
to
Google
for
this
project
for
this
program,
and
you
know
it's
like.
Basically:
are
they
keeping
up
with
their
work?
C
Are
they
doing
satisfactory
work
so
that'll
be,
and
that
shouldn't
be
too
hard
to
pass
that'll?
Be
you
know
if
you're
coming
to
the
meetings
and
getting
something
done
every
week,
you're
pretty
much
passed.
But
if
there
are
problems
with
like
you
know,
we
have
to
go
in
a
different
direction
or
if
you
know,
there's
some
problem
that
comes
up,
then
we
can
rescale
the
timeline,
but
I
mean
you
know.
C
We
want
to
basically
stick
that
the
timeline,
but
we
don't
want
to
you
know
if
there
are
things
that
can't
happen
for
some
reason
that
we
want
to
be
aware
of
those,
and
then
we
sort
of
calibrate
our
time
line.
So
I
wanted
to
just
mention
that,
because
I
know
that
I
always
tell
that
to
Summer
of
Code
students,
because
it
is
a
pretty
tight
time
line
and
we
do
have
a
lot
of
sort
of
milestones
later.
C
C
C
We
have
a
couple
of
tasks
here,
basically
involved,
as
well
as
a
marrow
board,
which
you
said
he
was
going
to
use
for
tracking
some
of
his
issues
and
then
assign
it
so
Krishna
I
talked
to
Krishna
Friday,
and
he
wants
to
do
this
thing
with
like
sort
of
a
general
biological
model
for
machine
learning
where
he
wants
to
look
at
like
all
different
types
of
images
like
medical
images,
plants
in
animal
microscopy
and
kind
of
use.
Those
in
a
way
that
would
allow
him
to
extract
some
very
general
features,
tag
told
them.
C
D
C
D
C
C
Mean
these
are
just
kind
of
like
placeholders
anyways.
This
is
ready.
We'll
just
do
like
you
know
all
right.
We
can
do
this
offline,
actually,
a
lot
of
them
populating
at
us.
I
just
wanted
to
put
a
couple
of
them
in
here
just
to
make
sure
we
have
them
for
and
then
yeah
that's,
oh
that's
good.
We
can.
We
have
those
in
there
so
that
so
now
we
have
some
of
those
in
to
do
and
I
think
you're
in
progress.
C
You
know
that
we're
kind
of
coming
up
on
and
we're
making
good
headway
on,
and
then
we
put
that
and
done
when
we're
done
so
this
one
actually
is
done
the
office
hours
discussion
section,
that's
something
we
did
I
think
two
weeks
ago,
where
we
talked
in
office
hours
and
slack
about
the
project
about
the
summer
project,
moving
movement,
tracking
machine
learning.
Why
don't
I
assign
that
to
this
will
be
so
that'll,
be
in
progress.
C
E
C
Yeah,
that's
that's
good
I!
Don't
know
why
you're
not
coming
up
as
a
collaborator.
Well,
yeah
we'll
see
yeah
so
I
mean
like
you
guys
want
to
add
to
this
board
yourself.
You
can
do
that
and
then
you
could
assign
yourself
into
tasks.
Otherwise
you
can
do
this
in
in
the
meeting,
but
I
rather
do
it
offline
actually,
and
then
this
is.
C
G
C
C
Susan
said
that
she
was
interested
in
sending
more
data
our
way
so
or
my
way,
so
that
we
can
do
more.
With
this.
We
haven't
we're
still
kind
of
on
that
issue
and
again
if
people
are
watching
online
or
in
the
meeting
here
are
interested
in
movie.
You
know
moving
this
forward.
It
can
move
this
up
tonight,
few
things
to
do
the
revisions
for
the
vessel
area
paper,
so
those
have
been
addressed.
I
was
addressing
when
this
week,
I
think
I
had
to
get
some
content
in
bushwell
and
I
got
I
I.
C
If
you
want
to
take
it
one
last
time,
I
can
send
a
Google
Doc
we
go
and
we
can
last
time.
But
if
there
hasn't
been
much
change,
was
this
some
small
changes
to
it,
but
that's
well
so
we'll
send
it
to
them
and
I
think
it's
accepted
at
this
point.
So
he
said
that
if
you
just
make
those
changes
that
we
accepted
and
so
so
that
one
I
think
we
can
just
put
it
and
finish
more
or
less.
C
Present
animal
keys
cell
systems
I'll
do
that
in
a
while,
but
that's
something
that
is
something
I'm
working
on:
revitalize
Fridays,
Coffee,
Hour
hackathon.
So
this
last
Friday
we
had
one
of
these
events,
Coffee
Hour
and
if
you're
interested
it's
at
4:00
p.m.
UTC,
which
is
a
late
morning
in
North
America
and
in
the
evening
I
think
in
India
and
in
Europe,
it's
probably
late
afternoon
early
evening.
So
we
do
it
at
a
different
link,
but
I
can
send
you
the
link
if
you're
interested,
otherwise
it's
in
our
slack
channel
often,
and
so
we
well.
C
C
You
know
sort
of
technical,
tying
loosens
together
meeting,
and
so
we
have.
Then
we
have
complexity
measures
which
is
a
different
issue.
This
is
something
that
Jesse
expressed
interest
in
last
week,
so
I
sent
out
an
email
with
some
information.
So
I
kind
of
this
is
something
that
Nick
and
I
talked
about
a
long
time
ago
and
I
put
together
some
things.
You
know
and
a
Google
Drive
directory
here,
so
these
are
things
that
I
found
in
sort
of
like
my
hard
drive,
folder
and
then
a
couple
of
things
that
I've
added
into
it.
C
So
this
is
this
was
initial
B
rch,
which
is
one
of
Dick's
codes
for
the
projects
he's
working
on,
but
this
is
so.
It
has
a
bunch
of
different
things
in
it.
There's
stuff
of
metabolic
scaling
information
measures,
some
stuff
on
differentiation
trees,
and
then
we
have
this
document
which
I,
don't
know,
look
like
something
that
was
like
started
and
yeah.
So
this
is
something
here.
C
Complexity,
measures
for
branching
structures
applied
to
differentiation,
trees
and
diatoms,
worse
news,
and
so
this
is
a
sort
of
I,
don't
know,
I
mean
it's
sort
of
a
static
sort
of
article
or
comment.
Let's
see
this
is
something
in
the
chat:
okay,
Nicko
log,
sergemichael
of
skis,
interested
in
complexity
measures,
so
yeah.
G
C
C
Or
in
the
number
of
papers
on
it,
so
we'll
actually
have
to
put
some
what
maybe
bring
him
into
the
loop
on
this
a
bit
come
see,
but
we're
kind
of
an
early
stages
of
this
so
I
mean
you
know,
kind
of
getting
on
the,
at
least
in
this
format,
the
create
a
doc
for
open
collaboration
papers.
That's
actually
done
because
I
put
that
up
on
the
readme
of
our
group
meetings
github.
So
if
we
go
to
group
meetings.
C
We
have
read
me
here,
and
this
contains
all
the
group
paper
links.
So
these
are
things
that,
if
you
find
interesting,
you
can
click
through
and
me
the
request
permissions
or
you
can
maybe
issue
a
pull
request.
If
it's
a
github
repo
or
you
know,
there's
some
what
you
can
submit
even
by
email,
if
that's
what's
more
comfortable
for
you.
C
G
C
I
think
that's
it
for
now,
I
think
things
community
rate
activities
for
G
sock,
that's
done
second
eyes
DeVos!
You
will
just
put
that
in
I
will
keep
that
in
here,
so
I
think
and
then
the
axolotl
montaging
is
in
on
hold
so
I.
Think
a
lot
of
this
stuff
is
just
kind
of
stuff
I
put
up
here
to
sort
of
small
over
and
think
about
what
it
will.
C
C
C
Okay,
any
interest
in
origin
of
life
blaze
shaped
droplets.
Well,
we
had
sowed
he
presented
on
this
a
couple
weeks
ago.
This
is
the
shape
droplets
work
that
he
was
presenting
on
and
why
don't
we
put
that
up?
Is
it
as
a
an
issue,
so
we
can
revisit
it,
but
if
you
haven't
seen
his
presence
and
I
would
go,
take
a
look
at
it.
I
think
it's
like
two
or
three
weeks
ago.
If
you
go
to
the
YouTube
channel,
you
look
at
the
videos.
C
So
we'll
put
that
in
cold.
Maybe
so
we
can
get
some
TV
if
someone's
interested
in
talking
butter.
That's
actually
what
I
was
gonna
present
on
the
the
multi
cell
systems,
but
I
didn't
do
that
every
week,
but
we'll
do
that
in
maybe
weeks
I
I
had
a
busy
week
last
week.
So
so
the
final
thing
I'd
like
to
talk
about
today
are
these
two
papers.
C
F
C
C
C
The
first
one
is
cell-cell
interaction
and
diversity
of
emergent
behaviors.
So
this
is
something
that
was
published
in
my
EEG
systems.
Biology,
and
this
is
so.
The
abstract
here
is.
Despite
myriads
of
possible
gene
expression
profiles,
cells
tend
to
be
found
in
a
confined
number
of
expression
patterns.
The
dynamics
of
boolean
models
of
gene
regulatory
networks
have
proven
to
be
a
likely
candidate
for
the
description
of
self
self-organization
phenomena,
so
they're
taking
the
gene
regulatory
networks
of
these
cells
and
they're
turning
them
into
boolean
models,
which
are
the
zero
one.
C
You
know
where
you
flip
it
and
that's
indicative
of
a
state
change,
because
cells
do
not
live
in
isolation,
but
they
constantly
shape
their
functions
to
adapt
to
signals
from
other
cells.
This
raises
the
question
of
whether
the
cooperation
among
cells
entails
an
expansion
or
reduction
of
their
possible
steady
states,
so
multi
random,
boolean
networks,
which
is
something
that
they
use,
are
introduced.
C
Chair,
is
a
model
for
interaction
among
cells
that
might
be
suitable
for
the
investigation
of
some
generic
properties
regarding
the
influence
of
communication
on
the
diversity
of
cell
behaviors,
so
they
have
I
think
we
talked
about
cell
cell
communication
a
couple
weeks
ago,
and
then
this
is
another
model
for
this.
This
is
what
they
go:
multi
random,
boolean
networks.
C
So,
in
spite
of
its
simplicity,
the
model
exhibits
a
non-obvious
phenomenon
according
to
which
a
moderate
exchange
of
products
among
G
stem
cells,
cluster
is
the
variety
of
possible
behaviors
and
so
and
I
guess
it
pushes
the
behavior
of
the
cells
towards
one
another.
So
basically,
the
cells
are
communicating
and
the
communication
modifies
the
cell
behavior
in
such
a
way,
so
that
it's
more
homogeneous
across
cells
and
so
and
then
a
more
invasive
coupling
would
lead
cells
towards
homogeny,
and
so,
let's
see
if
they
have
a
picture
of
her
diagram
with
this
model.
C
C
C
C
And
then,
let's
see
so
Stephen
Murray
says
Hoffman's
work
in
Wolfram's.
Work
relate
to
this
yeah
I.
Think
Kaufman
and
Wolfram
have
done
a
lot
of
work
on
this
type
in
this
direction.
The
Kaufman
with
Lake
and
K
landscapes,
which
are
these
landscapes
of
fitness
and
then
a
boolean
network,
so
they're
like
networks
of
different
nodes
that
have
a
boolean
state
of
zero
one
state
and
then
Wolfram's
doing
a
lot
of
stuff
with
like
networks
and
and
computational
complexity.
C
Now
you
wrote
that
huge
book
on
cellular
automata
but
he's
actually
moving
towards,
but
there
are
multi
way
systems
which
are
you
know
it's
like
a
network
but
they're
special
properties.
So
that's
interesting
that
sort
of
complexity
approach
and
then
this
is
a
paper
finally
they've
given
gaming,
it
you
know,
maybe
a
couple
minutes
here,
it's
probably
worth
more
than
that.
I
think
this
is
something
it's
Susan
sent
on:
zenefits
development
from
late
gastrulation
of
feeding
tadpole
in
simulated
microgravity.
So
this
is
not
modeling.
C
This
is
an
experimental
paper,
so
the
abstract
says:
microgravity
influence,
cytoskeletal
structure.
Well,
its
effects
on
cell
migration
are
not
well
understood
to
examine
the
effects
of
ultra
gravity
on
neural
crest,
cell
migration,
inserted
Xenopus
laevis
embryos,
which
is
a
frog
into
separate
microgravity
semi
semi
waiting,
slow
turning
lateral
vessels.
So
these
are
things
they.
These
are
actual
vessels
that
they
put
them
in
that
have
a
microgravity,
so
they
suspend
most
gravity,
there's
a
very
limited
amount
of
gravity
in
them
just
before
a
narration.
C
So
this
is
in
stage
11
to
12
of
the
frog
embryo.
So
this
is
different
than
the
C
elegans
embryo,
a
much
different
sort
of
developmental
set
of
stages
and
exposed
them
until
feeding
stage
stage
45
when
the
jaws
and
bronchial
apparatus
are
fully
functional,
so
they're,
basically
putting
in
microgravity
when
it's
forming
a
major
part
of
its
Anatomy
and
so
to
evaluate
us
related
artifacts
used
to
different
as
T
Ovie's
and
a
vibration
control,
as
well
as
a
stationary
control
vessel,
so
they're
controlling
for
effects.
C
They
have
vibration
and
things
like
that,
so
Susan
Crawford,
yeah
Susan,
says
the
vibration
of
the
vessels
had
an
influence
on
the
neural
crest
by
itself.
Yeah!
That's
why
they
did
the
control
and
that's
Latin
and
cell
biology.
They
have
wings.
You
know
they
do
controls
for
things
like
that.
Because
it'll
be
you
know,
though
you
can't
rule
out.
C
The
to
STL
V's,
often
Ile,
the
different
or
conflicting
results.
Many
differences,
such
as
increased
cartilage
size,
attenuated
pops,
a
to
expression,
an
increased
cell
division
may
be
attributed
mainly
to
vibration.
Of
the
rotating
vessels.
However,
tadpoles
are
developed
in
simulated
microgravity,
both
STL
V's,
but
not
the
vibration
control
showed
significantly
more
skeletal
abnormalities.
The
stronger
effects
on
cartilages
derived
from
NCC's
those
derived
mainly
from
mesoderm.
We
conclude
that
migrating
NCC's
of
Xenopus
are
sensitive
to
the
ultra
gravitational
environment,
and
studies
are
relying
in
bioreactors
to
simulate.
C
C
Yeah
my
work
on
vibration
needs
to
be
done.
Yeah
I
think
that's
in
developing
embryos,
so
yeah
I
mean
there's
a
lot
of
like
I
know
that
there's
a
lot
of
some
work
that
people
have
done
on
like
stem
cell
differentiation
in
force,
forces
and
cells.
So
in
other
words
like
they
have
they've
done
work
where
they've
like
looked
at
like
what,
if
they
implement
forces
on
cells
like
rotational
forces
or
sometimes
but
put
them
on
different
surfaces
in
the
culture
dish,
and
they
have
to
adhere
to
the
different
surfaces.
C
Furthermore,
they
can
add,
like
forces
to
the
culture,
and
they
can
actually
observe
changes
in
how
differentiation
the
differentiation
program
unfolds,
and
we
know
that
stem
cells
are
what
they
call
multipotent.
So
they
can
go
down
a
number
of
different
pathways,
not
only
of
like
regular,
like
somatic
cells,
but
they
can
also
go
down
like
cancer
pathways.
C
Just
because
you
know
when
you
they
have
a
normal
sort
of
program,
but
they
have
to
have
environmental
factors
that
also
contribute
to
their
differentiation,
and
so
when
they
don't
get
the
ones
that
they're
used
to
in
development,
they
can
go
down
different
pathways.
You
can
induce
all
sorts
of
things.
C
C
F
C
Like
really
the
physics
of
fluids
in
that
sort
of
stuff
yeah,
so
it's
yeah,
it's
that
it's
interesting
yeah
I
mean
that
I
think
people
look
at
that
like
they
think
they
know
there's
something
going
on
there,
but
no
one
really
knows
what
it
is,
and
you
know
it's
it's
that
cells,
of
course
sensitive
vironment,
but
they
go
beyond
that
and
like
people
have
never
been
able
to
go
beyond
that,
I.
Don't
think,
at
least
in
terms
of
you
know,
predictive
model.
C
Yeah
a
force
due
to
fluid
movement
yeah
exactly
so.
This
is
you
know,
and
your
you
have
a
cell
on
a
bunch
of
cells
in
a
fluid
which
they
are,
of
course
in
biology.
You
have
these
forces
and
they,
of
course,
have
an
effect
on
the
cells
of
their
development
and
then,
in
you
know,
cells.
Would,
though,
you
know,
though,
experience
forces
their
fluids
flowing
through
your
body
all
the
time,
but
like
sometimes
those
forces
are
not
what
is
normal
in
the
normal
operating
range
and
so.
C
C
C
Okay,
that's
fine
yeah
yeah,
it's
yeah!
Well,
we
try
to
be
pretty
accommodating.
We
have
a
lot
of
technical
issues,
as
you
can
tell
from
today,
but
yeah
I.
Think
that's
good
thanks
for
everyone
for
a
meeting
today
we're
past
the
top
of
the
hour.
So
they've
got
to
go
to
another
meeting
so
but
we'll
be
on
next
week.
Yeah
stay
safe,
have
a
good
week
and
talk
to
you
later
next.