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s
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F
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m
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ly
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sin
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ra
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S
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C
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b
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c
s
a
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ly
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v
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p
ro
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tes
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c
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d
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d
d
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v
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lo
p
m
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t
o
f
v
a
c
c
in
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s.
K
ey
w
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d
s
:
C
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s
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v
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s
eq
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I
m
m
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b
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f
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r
m
atics
L
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Pro
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ca
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m
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1
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s
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ca
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b
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a
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g
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C
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2
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4
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m
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s
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lo
b
all
y
[
1
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.
Ad
d
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ally
,
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W
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Hea
lth
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p
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id
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ates
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[
2
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,
s
u
g
g
esti
n
g
th
at
th
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r
em
ain
s
p
o
ten
tial f
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On
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in
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s
p
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is
th
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v
ac
cin
atio
n
p
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o
ce
s
s
[
3
]
,
[
4
]
.
T
o
d
eter
m
i
n
e
v
ac
cin
e
ca
n
d
id
ates,
it
is
ess
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tial
to
p
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s
s
s
eq
u
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d
ata
f
r
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m
v
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s
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.
An
ap
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Evaluation Warning : The document was created with Spire.PDF for Python.
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6
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f
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eq
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ca
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as v
ac
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n
e
ca
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d
id
ates f
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r
r
elate
d
v
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s
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[
5
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–
[
7
]
.
T
h
is
s
tu
d
y
co
m
b
i
n
ed
b
io
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n
f
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m
atics
a
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am
ely
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u
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b
io
in
f
o
r
m
atics
[
8
]
–
[
1
2
]
.
B
io
in
f
o
r
m
atics
a
n
aly
s
is
was
p
er
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m
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y
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s
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h
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en
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s
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ed
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e
x
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g
d
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y
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o
n
u
cleic
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DNA
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s
eq
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s
;
if
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e
ar
e
m
o
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th
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is
ca
lled
m
u
ltip
le
s
eq
u
en
ce
alig
n
m
en
t
[
1
3
]
–
[
1
6
]
.
T
h
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p
r
o
ce
s
s
d
eter
m
in
es
th
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elatio
n
s
h
ip
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s
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m
e
v
ir
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s
v
ar
ian
ts
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wh
ich
ca
n
b
e
in
th
e
f
o
r
m
o
f
a
p
h
y
lo
g
en
etic
tr
ee
[
1
7
]
–
[
2
1
]
,
m
u
tatio
n
s
eq
u
en
c
es
in
v
ir
u
s
v
ar
ian
ts
,
o
r
th
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eter
m
in
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f
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er
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d
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,
n
am
ely
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s
eq
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th
at
d
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th
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er
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Fo
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n
m
en
ts
an
d
co
n
s
er
v
ed
s
eq
u
e
n
ce
s
,
a
s
p
ec
ialized
m
eth
o
d
is
r
eq
u
ir
ed
to
d
eter
m
in
e
th
eir
p
o
s
itio
n
s
.
I
n
co
n
tr
ast
to
p
r
ev
io
u
s
s
tu
d
ies
[
2
2
]
–
[
2
4
]
an
d
s
tu
d
ies
r
elate
d
to
th
e
al
g
o
r
i
th
m
u
s
ed
[
2
5
]
p
r
o
p
o
s
ed
th
e
J
av
a
p
atter
n
f
in
d
er
(
J
aPaFi)
m
eth
o
d
,
i
n
wh
ich
it
is
d
if
f
icu
lt
t
o
f
i
n
d
a
co
n
s
er
v
ed
s
eq
u
e
n
ce
u
s
in
g
th
e
alg
o
r
,
th
is
s
tu
d
y
u
s
es
a
co
m
b
in
atio
n
o
f
p
r
o
g
r
ess
iv
e
alig
n
m
en
t
an
d
B
o
o
lean
l
o
g
ic
to
o
v
er
c
o
m
e
th
is
lim
it
atio
n
.
I
n
p
r
ev
io
u
s
s
tu
d
ies
[
2
6
]
–
[
2
8
]
,
B
o
o
lean
lo
g
ic
was
d
escr
ib
e
d
as
a
way
t
o
test
a
v
alu
e
as
tr
u
e
o
r
f
alse,
y
es
o
r
n
o
,
an
d
i
n
n
u
m
er
ical
ter
m
s
,
as
1
o
r
0
.
Du
r
in
g
its
d
ev
elo
p
m
en
t,
B
o
o
lean
lo
g
ic
o
p
er
atio
n
s
wer
e
clo
s
ely
r
elate
d
to
s
witch
in
g
n
eu
r
al
n
etwo
r
k
s
[
2
9
]
,
wh
ich
wer
e
later
f
u
r
th
e
r
d
ev
elo
p
ed
u
n
d
er
th
e
n
am
e
l
o
g
i
c
lear
n
in
g
m
ac
h
in
e
(
L
L
M)
[
3
0
]
–
[
3
2
]
.
T
h
e
au
t
h
o
r
s
[
3
0
]
‒
[
3
2
]
s
h
o
wed
t
h
at
LLM
s
wer
e
im
p
lem
en
ted
as
f
o
r
m
u
la
-
b
ased
class
if
icatio
n
u
s
in
g
s
witch
in
g
n
eu
r
al
n
etwo
r
k
s
.
T
h
er
ef
o
r
e,
u
s
in
g
an
L
L
M,
th
e
s
im
ilar
ity
b
etwe
en
th
e
s
eq
u
en
ce
s
in
th
e
alig
n
m
en
t
r
esu
lts
ca
n
b
e
test
ed
.
T
h
e
m
a
in
o
b
jectiv
e
o
f
th
is
r
esear
c
h
is
to
ass
is
t
in
th
e
in
itial st
ag
es
o
f
v
ac
cin
e
-
r
elate
d
r
esear
ch
,
n
am
ely
,
d
ete
r
m
in
i
n
g
th
e
f
o
cu
s
o
f
th
e
s
eq
u
en
ce
s
ec
tio
n
b
ein
g
s
tu
d
ied
in
th
e
lab
o
r
at
o
r
y
.
T
h
is
o
b
jectiv
e
n
ee
d
s
to
b
e
s
u
p
p
o
r
ted
b
y
an
im
m
u
n
o
in
f
o
r
m
atics
ap
p
r
o
ac
h
u
s
ed
to
id
e
n
tif
y
v
ac
cin
e
ca
n
d
id
ates
o
b
tain
ed
in
s
ilico
.
B
ased
o
n
r
elate
d
r
esear
ch
[
3
3
]
‒
[
3
6
]
r
eg
ar
d
in
g
p
e
p
tid
es
in
co
n
s
er
v
ed
s
eq
u
en
ce
s
,
th
er
e
is
n
o
s
p
ec
if
ic
m
eth
o
d
in
th
eir
r
esear
ch
f
o
r
o
b
tain
i
n
g
c
o
n
s
er
v
e
d
s
eq
u
en
ce
s
f
o
r
f
u
r
th
er
im
m
u
n
o
in
f
o
r
m
atics.
T
o
ad
d
r
ess
th
ese
p
r
o
b
lem
s
,
we
p
r
o
p
o
s
e
an
alg
o
r
ith
m
t
h
at
co
m
b
in
es
p
r
o
g
r
ess
iv
e
alig
n
m
en
t
an
d
an
L
L
M
to
d
ete
r
m
in
e
th
e
p
o
s
itio
n
o
f
co
n
s
er
v
e
d
s
eq
u
en
ce
s
at
b
o
th
th
e
DNA
an
d
p
r
o
tein
lev
els.
T
h
is
ap
p
r
o
ac
h
lev
e
r
ag
es
th
e
s
tr
en
g
th
s
o
f
s
eq
u
en
ce
alig
n
m
en
t
an
d
B
o
o
lean
lo
g
ic
o
p
e
r
atio
n
s
to
id
en
tify
co
n
s
er
v
ed
s
eq
u
e
n
ce
s
cr
itical
f
o
r
v
ac
cin
e
d
e
v
elo
p
m
e
n
t.
B
y
in
teg
r
atin
g
b
i
o
in
f
o
r
m
atics
an
d
im
m
u
n
o
in
f
o
r
m
atics
an
aly
s
es,
th
e
m
eth
o
d
n
o
t o
n
l
y
en
h
an
ce
s
th
e
ac
cu
r
ac
y
o
f
co
n
s
er
v
ed
r
eg
io
n
id
en
tific
atio
n
b
u
t
also
f
ac
ilit
ate
s
th
e
ea
r
ly
d
etec
tio
n
o
f
p
r
o
m
is
in
g
v
ac
cin
e
ca
n
d
id
ates.
T
h
is
d
u
al
ap
p
r
o
ac
h
en
s
u
r
es
a
m
o
r
e
e
f
f
icien
t
an
d
tar
g
eted
id
en
tific
atio
n
p
r
o
ce
s
s
,
s
ig
n
if
ican
tly
co
n
tr
ib
u
tin
g
to
t
h
e
ex
p
ed
ited
d
ev
el
o
p
m
en
t
o
f
v
ac
ci
n
es
ag
ain
s
t
r
ap
id
ly
ev
o
lv
in
g
v
ir
u
s
es.
T
h
e
r
em
ain
d
er
o
f
th
is
p
ap
er
i
s
s
tr
u
ctu
r
ed
as
f
o
llo
ws
.
Sectio
n
2
p
r
esen
ts
th
e
p
r
o
p
o
s
ed
m
eth
o
d
o
lo
g
y
.
Sectio
n
3
p
r
esen
ts
th
e
ex
p
e
r
i
m
en
tal
r
esu
lts
,
in
clu
d
in
g
th
e
e
v
alu
atio
n
o
f
p
r
o
p
o
s
ed
m
eth
o
d
o
n
v
ir
al
s
eq
u
e
n
ce
s
an
d
th
eir
v
ar
ian
ts
,
as we
ll a
s
th
e
im
m
u
n
o
in
f
o
r
m
atics a
n
aly
s
is
.
Fin
ally
,
s
ec
tio
n
4
co
n
cl
u
d
es th
e
p
ap
er
.
2.
M
E
T
H
O
D
T
h
e
m
ain
aim
o
f
th
is
s
tu
d
y
w
as
to
id
en
tif
y
c
o
n
s
er
v
ed
s
eq
u
en
ce
s
th
at
ar
e
s
u
b
s
eq
u
e
n
ce
s
o
f
th
e
m
ain
s
eq
u
en
ce
an
d
ca
n
b
e
p
r
o
ce
s
s
ed
f
u
r
th
e
r
f
o
r
im
m
u
n
o
in
f
o
r
m
atics
an
aly
s
is
.
T
h
e
d
eter
m
in
atio
n
o
f
co
n
s
er
v
e
d
s
eq
u
en
ce
s
u
s
ed
th
e
p
r
o
p
o
s
e
d
m
eth
o
d
.
T
h
e
im
m
u
n
o
i
n
f
o
r
m
atics
an
aly
s
is
u
s
in
g
th
at
m
eth
o
d
co
n
s
is
ted
o
f
s
ev
er
al
s
tag
es,
as sh
o
wn
in
Fig
u
r
e
1
.
T
h
e
s
tag
es
ar
e
e
x
p
lain
ed
in
th
e
f
o
llo
win
g
s
tep
s
:
i)
C
o
llectin
g
s
eq
u
en
ce
d
ata
f
o
r
a
n
aly
s
is
.
ii)
Pre
p
r
o
ce
s
s
in
g
d
ata
b
y
an
aly
z
in
g
th
e
m
u
tatio
n
u
s
in
g
Nee
d
l
em
an
-
W
u
n
s
ch
alig
n
m
e
n
t
an
d
tr
an
s
f
o
r
m
in
g
th
e
d
ata
in
to
g
en
etic
d
is
tan
ce
v
alu
es u
s
in
g
th
e
Kim
u
r
a
m
o
d
e
l.
iii)
Pro
ce
s
s
in
g
g
en
etic
d
is
tan
ce
v
alu
es
in
to
th
e
f
o
r
m
o
f
a
p
h
y
lo
g
e
n
etic
tr
ee
u
s
in
g
t
h
e
n
eig
h
b
o
r
-
jo
in
in
g
alg
o
r
ith
m
as a
g
u
id
e
tr
ee
a
n
d
p
r
o
g
r
ess
iv
e
alig
n
m
en
t to
p
er
f
o
r
m
m
u
ltip
le
s
eq
u
e
n
ce
alig
n
m
e
n
t.
iv
)
C
o
m
b
in
in
g
p
r
o
g
r
ess
iv
e
alig
n
m
en
t a
n
d
L
L
M
to
d
eter
m
in
e
t
h
e
co
n
s
er
v
e
d
s
eq
u
en
ce
.
v)
E
x
p
er
im
en
ts
o
n
r
ea
l
v
ir
u
s
d
ata
u
s
in
g
an
in
s
ilico
m
eth
o
d
t
o
d
is
co
v
er
p
ep
tid
es
as v
ac
cin
e
ca
n
d
id
ates
with
im
m
u
n
o
in
f
o
r
m
atics a
n
aly
s
is
u
s
in
g
B
ep
i
P
r
ed
2
.
0
a
n
d
Vax
iJ
e
n
v
2
.
0
.
2
.
1
.
B
io
info
r
m
a
t
ics
a
na
ly
s
is
:
co
ns
er
v
ed
s
equence
2
.
1
.
1
.
Nee
dlem
a
n
-
Wun
s
ch
a
l
ig
nm
ent
Nee
d
lem
an
-
W
u
n
s
ch
alig
n
m
e
n
t
is
a
m
eth
o
d
f
o
r
o
b
tain
in
g
th
e
o
p
tim
al
o
v
er
all
g
lo
b
al
alig
n
m
en
t
b
etwe
en
two
s
elec
ted
s
eq
u
en
ce
s
[
3
7
]
.
Su
p
p
o
s
e
th
e
r
e
ar
e
two
s
eq
u
en
ce
s
,
=
1
,
2
,
⋯
,
an
d
=
1
,
2
,
⋯
,
.
A
m
at
r
ix
o
f
o
r
d
er
(
+
1
)
(
+
1
)
is
f
o
r
m
ed
.
T
h
e
elem
e
n
ts
in
t
h
e
-
th
r
o
w
an
d
-
th
co
lu
m
n
,
(
,
)
,
f
o
r
1
<
<
an
d
1
<
<
ar
e
th
e
s
am
e
as
th
e
o
p
tim
al
alig
n
m
en
t
s
co
r
es
b
etwe
e
n
1
,
2
,
⋯
,
an
d
1
,
2
,
⋯
,
.
T
h
e
elem
en
t
(
,
0
)
f
o
r
1
<
<
is
th
e
s
co
r
e
o
f
th
e
alig
n
m
en
t
b
etwe
en
1
,
2
⋯
,
an
d
th
e
g
ap
alo
n
g
.
L
ik
ewis
e,
f
o
r
E
lem
en
t
(
0
,
)
,
1
<
<
is
th
e
s
co
r
e
o
f
th
e
alig
n
m
en
t
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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tell
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-
8
9
3
8
I
mmu
n
o
-
b
i
o
in
fo
r
ma
tics
a
n
a
ly
s
is
o
f p
r
o
g
r
ess
ive
a
lig
n
men
t a
n
d
lo
g
ic
le
a
r
n
in
g
ma
c
h
in
e
…
(
F
elza
R
id
h
o
)
3191
b
etwe
en
1
,
2
,
⋯
,
an
d
th
e
g
ap
alo
n
g
.
T
h
e
m
atr
ix
is
co
n
s
tr
u
cte
d
ite
r
ativ
ely
,
s
tar
tin
g
with
(
0
,
0
)
=
0
.
E
ac
h
elem
en
t
o
f
t
h
e
m
atr
ix
is
f
illed
f
r
o
m
th
e
to
p
-
lef
t
to
t
h
e
b
o
tto
m
-
r
ig
h
t.
I
f
(
−
1
,
−
1
)
,
(
−
1
,
)
,
an
d
(
,
−
1
)
ar
e
k
n
o
wn
,
(
,
)
ca
n
b
e
c
o
m
p
u
te
d
u
s
in
g
(
1
)
.
(
,
)
=
{
(
−
1
,
−
1
)
+
(
,
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,
(
−
1
,
)
+
(
,
−
)
,
(
,
−
1
)
+
(
−
,
)
}
(
1
)
W
h
en
ca
lcu
latin
g
(
,
)
,
th
e
d
ir
ec
tio
n
in
wh
ich
(
,
)
is
o
b
tain
ed
i
s
s
to
r
ed
.
Af
ter
o
b
tain
i
n
g
(
,
)
,
b
ac
k
tr
ac
k
in
g
was p
er
f
o
r
m
ed
t
o
o
b
tain
t
h
e
o
p
tim
al
alig
n
m
en
t
.
(
,
)
is
r
ep
r
esen
ted
as th
e
alig
n
m
en
t sco
r
e.
Fig
u
r
e
1
.
Pro
p
o
s
ed
m
et
h
o
d
f
o
r
o
b
tain
in
g
co
n
s
er
v
e
d
s
eq
u
en
ce
an
d
im
m
u
n
o
-
b
io
in
f
o
r
m
atics a
n
aly
s
is
Af
ter
alig
n
m
en
t,
th
e
two
alig
n
ed
s
eq
u
en
ce
s
ar
e
ex
p
r
ess
ed
as
′
=
1
′
,
2
′
,
⋯
,
ℎ
′
an
d
′
=
1
′
,
2
′
,
⋯
ℎ
′
.
A
d
if
f
er
en
t
p
ar
t
o
f
th
e
s
eq
u
en
ce
was
u
s
ed
th
at
ch
an
g
e
d
th
e
n
u
cleo
tid
e
f
r
o
m
th
e
f
i
r
s
t
s
eq
u
en
ce
to
th
e
s
ec
o
n
d
s
eq
u
e
n
ce
,
wh
ich
is
ca
ll
a
m
u
tatio
n
.
T
h
e
m
u
tatio
n
s
u
s
ed
wer
e
d
iv
i
d
ed
in
to
tr
a
n
s
itio
n
s
an
d
tr
an
s
v
er
s
io
n
s
[
3
8
]
.
A
tr
an
s
itio
n
is
a
ch
an
g
e
in
a
n
u
cleo
t
id
e
to
an
o
th
er
n
u
cleo
tid
e
in
a
s
im
ilar
b
ase
o
r
th
e
ch
an
g
e
o
f
A
→
G,
G
→
A,
C
→
T
,
an
d
T
→
C
an
d
tr
an
s
v
er
s
io
n
is
a
ch
an
g
e
in
a
n
u
cleo
tid
e
to
an
o
th
er
n
u
cleo
tid
e
in
an
u
n
s
im
ilar
b
ase;
th
e
ch
a
n
g
es
ar
e
A
→
C
,
A
→
T
,
C
→
A,
C
→
G,
G
→
C
,
G
→
T
,
T
→
A,
an
d
T
→
G.
T
h
e
p
r
o
ce
s
s
f
o
r
d
eter
m
in
in
g
th
e
n
u
m
b
er
o
f
tr
an
s
itio
n
s
an
d
tr
an
s
v
er
s
i
o
n
s
is
p
r
esen
ted
in
Alg
o
r
ith
m
1
.
T
h
e
n
u
m
b
e
r
o
f
m
u
tatio
n
s
in
Alg
o
r
ith
m
1
ca
n
th
en
b
e
u
s
ed
to
ap
p
ly
Kim
u
r
a
’
s
m
o
d
el.
Alg
o
r
ith
m
1
.
Fin
d
in
g
t
h
e
o
cc
u
r
r
en
ce
o
f
tr
an
s
itio
n
s
an
d
tr
an
s
v
er
s
io
n
s
inputs: Sequence
′
, Sequence
′
, Sequence length
ℎ
output: Number of transitions
and transversions
procedure transition_transversion
(
′
,
′
)
Determine
and
array in h length;
=
1
,
2
,
⋯
,
ℎ
;
=
1
,
2
,
⋯
,
ℎ
;
Convert the elements of
and
into
0
and
1
;
for
′
,
′
,
=
1
,
2
,
⋯
,
ℎ
do
if
′
=
A and
′
=
C or
′
=
C and
′
=
A or
′
=
G and
′
=
T or
′
=
T and
′
=
G then
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2252
-
8
9
3
8
I
n
t J Ar
tif
I
n
tell
,
Vo
l.
15
,
No
.
4
,
Au
g
u
s
t 2
0
2
6
:
3
1
8
9
-
3
2
0
1
3192
=
1
;
else
=
0
;
end
if
′
=
A
an
d
′
=
G
or
′
=
A
an
d
′
=
T
or
′
=
G
an
d
′
=
A
or
′
=
G
an
d
′
=
C
or
′
=
C
an
d
′
=
G or d'_i=C and
′
=
T or
′
=
T and
′
=
A or
′
=
T and
′
=
C then
=
1
;
else
=
0
;
end
end
Determine the number of transitions
and transversions
;
=
∑
;
=
∑
;
end
2
.
1
.
2
.
K
im
ura
m
o
del
T
h
e
Kim
u
r
a
m
o
d
el
was
ap
p
lied
to
o
b
tain
th
e
d
is
tan
ce
m
atr
ix
b
etwe
en
th
e
two
s
eq
u
en
ce
s
.
T
h
e
d
is
tan
ce
m
atr
ix
was
cr
ea
ted
u
s
in
g
th
is
m
o
d
el.
T
h
e
m
o
d
el
f
o
r
cr
ea
tin
g
th
e
d
is
tan
ce
m
atr
ix
is
ex
p
r
ess
ed
as
f
o
llo
ws
[
3
9
]
:
‒
Def
in
itio
n
1
.
I
f
P
n
u
m
b
e
r
o
f
tr
an
s
itio
n
s
o
cc
u
r
r
in
g
b
etwe
e
n
two
s
eq
u
en
ce
s
,
an
d
Q
is
t
h
e
n
u
m
b
e
r
o
f
tr
an
s
v
er
s
io
n
s
th
at
o
cc
u
r
.
T
h
e
d
is
tan
ce
b
etwe
en
two
s
eq
u
en
c
es is
d
ef
in
ed
as
(
2
)
.
,
=
−
1
2
(
(
1
−
2
,
−
,
)
√
1
−
2
,
)
(
2
)
Af
ter
o
b
tain
in
g
th
e
v
alu
e
an
d
f
o
r
m
in
g
a
d
is
tan
ce
m
atr
ix
,
th
e
d
is
tan
ce
m
atr
ix
was
u
s
e
d
to
f
o
r
m
a
p
h
y
lo
g
en
etic
tr
ee
u
s
in
g
th
e
n
ei
g
h
b
o
r
-
jo
in
in
g
alg
o
r
ith
m
.
2
.
1
.
3
.
Neig
hb
o
r
-
j
o
ini
ng
a
lg
o
rit
hm
T
h
e
n
eig
h
b
o
r
-
jo
in
in
g
alg
o
r
ith
m
was
u
s
ed
to
co
n
s
tr
u
ct
a
p
h
y
lo
g
en
etic
tr
ee
f
r
o
m
s
eq
u
en
ce
d
is
tan
ce
s
.
T
h
e
m
eth
o
d
iter
ativ
ely
co
m
p
u
tes
a
co
r
r
ec
tio
n
ter
m
f
r
o
m
th
e
d
is
tan
ce
m
at
r
ix
,
th
en
s
elec
ts
th
e
p
air
with
th
e
s
m
allest
,
=
,
−
−
[
3
9
]
.
T
h
at
p
air
is
m
er
g
ed
in
to
a
n
ew
o
p
er
atio
n
al
tax
o
n
o
m
ic
u
n
it
(
OT
U)
,
an
d
d
is
tan
ce
s
ar
e
r
ec
alcu
lated
.
T
h
is
p
r
o
ce
s
s
is
r
ep
ea
ted
u
n
til
o
n
ly
th
r
ee
OT
Us
r
em
ain
.
T
h
e
r
esu
ltin
g
tr
ee
th
en
s
er
v
ed
as a
g
u
id
e
tr
ee
f
o
r
p
r
o
g
r
ess
iv
e
alig
n
m
en
t.
2
.
1
.
4
.
P
ro
g
re
s
s
iv
e
a
lig
nm
ent
T
h
e
im
p
lem
e
n
tatio
n
u
s
ed
p
r
o
g
r
ess
iv
e
alig
n
m
en
t
,
a
m
u
ltip
l
e
-
s
eq
u
en
ce
alig
n
m
en
t
h
eu
r
is
tic.
Star
tin
g
with
two
s
eq
u
en
ce
s
alig
n
ed
,
a
th
ir
d
is
ad
d
ed
an
d
alig
n
ed
,
an
d
th
e
p
r
o
ce
s
s
r
ep
ea
ts
u
n
til
all
s
eq
u
en
ce
s
ar
e
in
clu
d
ed
,
g
u
id
ed
b
y
a
p
h
y
lo
g
en
etic
tr
ee
b
u
ilt
f
r
o
m
Kim
u
r
a
-
b
ased
p
air
wis
e
d
is
tan
ce
s
[
3
9
]
.
T
h
e
r
esu
lt
is
a
m
u
ltip
le
s
eq
u
en
ce
alig
n
m
en
t,
f
o
r
m
ally
d
ef
in
e
d
as
an
ex
p
a
n
s
io
n
o
f
t
h
e
o
r
ig
in
al
s
eq
u
en
ce
s
with
in
s
er
ted
g
ap
s
s
u
ch
th
at
all
ex
p
a
n
d
ed
s
eq
u
e
n
ce
s
h
av
e
th
e
s
am
e
len
g
th
,
a
n
d
n
o
co
lu
m
n
c
o
n
s
is
ts
en
tire
ly
o
f
g
ap
s
.
B
ec
au
s
e
alig
n
m
en
t
alo
n
e
ca
n
n
o
t
p
in
p
o
in
t
co
n
s
er
v
e
d
r
eg
i
o
n
s
,
we
c
o
m
b
in
ed
t
h
e
alig
n
m
e
n
t
o
u
tp
u
t
with
a
LLM
to
id
en
tify
co
n
s
er
v
ed
s
eq
u
en
ce
p
o
s
itio
n
s
.
2
.
1
.
5
.
L
o
g
ic
lea
rning
m
a
chin
e
I
n
th
is
s
tu
d
y
,
a
L
L
M
was
em
p
lo
y
ed
as
an
ef
f
icien
t
im
p
le
m
en
tatio
n
o
f
a
s
witch
in
g
n
eu
r
al
n
etwo
r
k
m
o
d
el
to
d
eter
m
in
e
th
e
p
o
s
itio
n
o
f
th
e
co
n
s
er
v
ed
s
eq
u
e
n
c
e
[
2
9
]
.
LLM
s
u
s
e
latticizatio
n
,
wh
ich
is
clo
s
ely
r
elate
d
to
lo
g
ic
test
in
g
.
T
h
e
r
esu
lts
o
f
th
is
tes
t
ar
e
b
ased
o
n
B
o
o
lean
lo
g
ic,
an
d
th
e
o
u
tp
u
t
o
f
latticizatio
n
is
{
0
,
1
}
.
I
n
B
o
o
lean
alg
eb
r
a,
lo
g
ic
l
ev
els
ar
e
r
ep
r
esen
ted
b
y
s
y
m
b
o
ls
,
m
ak
in
g
it
a
ty
p
e
o
f
l
o
g
ic
alg
eb
r
a.
Alth
o
u
g
h
a
n
y
s
y
m
b
o
l
ca
n
b
e
u
s
ed
,
alp
h
ab
etic
letter
s
ar
e
th
e
m
o
s
t
f
r
eq
u
e
n
tly
u
s
ed
.
A
n
y
letter
u
s
ed
as
a
v
ar
iab
le
ca
n
h
av
e
a
v
alu
e
o
f
1
o
r
0
,
b
ec
au
s
e
lo
g
ic
lev
els
ar
e
o
f
ten
r
ep
r
esen
ted
b
y
s
y
m
b
o
ls
1
an
d
0
.
B
o
o
lea
n
lo
g
ic
o
p
er
atio
n
s
ar
e
d
e
f
in
ed
as
f
o
llo
ws
[
4
0
]
.
‒
Def
in
itio
n
2
.
B
o
o
lean
alg
eb
r
a
is
an
alg
eb
r
a
ℬ
=
(
,
∧
,
∨
,
¯
,
0
,
1
)
with
ty
p
e
(
2
,
2
,
1
,
0
,
0
)
wh
ich
s
atis
f
ies
th
e
f
o
llo
win
g
c
o
n
d
itio
n
s
:
i)
(
,
∧
,
∨
)
is
d
is
tr
ib
u
tiv
e,
wh
ich
h
as 0
as th
e
s
m
allest ele
m
en
t a
n
d
1
as
th
e
lar
g
est ele
m
en
t
.
ii)
¯
∶
→
is
a
u
n
ar
y
o
p
e
r
ato
r
s
o
is
th
e
c
o
m
p
lem
en
t
of
f
o
r
∈
.
T
h
e
∧
o
p
er
ato
r
is
also
k
n
o
wn
as
th
e
AND
o
p
er
ato
r
,
an
d
∨
is
k
n
o
wn
as
th
e
OR
o
p
er
ato
r
.
T
h
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
is
o
b
tain
e
d
b
y
p
e
r
f
o
r
m
in
g
B
o
o
lean
al
g
e
b
r
a
o
n
′
s
eq
u
en
ce
s
.
B
o
o
lean
lo
g
ic
o
p
er
atio
n
s
ar
e
p
er
f
o
r
m
ed
f
o
r
ev
er
y
c
o
m
b
in
atio
n
o
f
,
,
wh
er
e
=
1
,
2
,
3
,
⋯
,
an
d
=
1
,
2
,
3
⋯
,
with
th
e
c
o
n
d
itio
n
>
;
th
u
s
,
th
e
r
e
a
r
e
m
a
n
y
B
o
o
lean
lo
g
ic
s
eq
u
en
ce
s
in
t
h
e
f
ir
s
t
s
tag
e,
to
talin
g
th
e
co
m
b
in
atio
n
2
=
!
(
−
2
)
!
2
!
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ar
tif
I
n
tell
I
SS
N:
2252
-
8
9
3
8
I
mmu
n
o
-
b
i
o
in
fo
r
ma
tics
a
n
a
ly
s
is
o
f p
r
o
g
r
ess
ive
a
lig
n
men
t a
n
d
lo
g
ic
le
a
r
n
in
g
ma
c
h
in
e
…
(
F
elza
R
id
h
o
)
3193
T
h
e
B
o
o
lean
lo
g
ic
r
esu
lts
in
th
e
in
itial
s
tag
e
ar
e
ex
p
r
ess
ed
as
=
{
,
1
,
,
2
,
⋯
,
,
,
⋯
,
,
}
,
,
=
{
0
,
1
}
,
wh
er
e
=
1
,
2
,
3
,
⋯
,
2
,
l
is
th
e
s
eq
u
en
ce
p
o
s
itio
n
,
an
d
m
is
th
e
s
eq
u
en
ce
le
n
g
th
.
,
h
as
a
v
alu
e
o
f
0
if
th
e
two
co
m
p
ar
ed
′
=
,
1
′
,
,
2
′
,
⋯
,
,
′
,
⋯
,
,
′
an
d
′
=
,
1
′
,
,
2
′
,
⋯
,
,
′
,
⋯
,
,
′
s
eq
u
en
ce
elem
en
ts
in
p
o
s
itio
n
ar
e
n
o
t
th
e
s
am
e
an
d
,
h
as
a
v
alu
e
o
f
1
if
th
e
co
m
p
a
r
ed
′
an
d
′
s
eq
u
en
ce
elem
en
ts
in
p
o
s
itio
n
h
av
e
th
e
s
am
e
v
alu
e.
T
h
er
ef
o
r
e,
i
n
a
cc
o
r
d
an
ce
with
th
e
latticizatio
n
o
f
B
o
o
lean
lo
g
ic,
th
e
r
esu
lt
at
th
is
s
tag
e
is
{
0
,
1
}
2
.
I
n
th
e
co
n
tex
t
o
f
class
if
icatio
n
,
let
∈
ℜ
r
ep
r
esen
t
a
-
d
im
en
s
io
n
al
ex
am
p
le
th
at
n
ee
d
s
to
b
e
lab
eled
with
a
ca
teg
o
r
ical
o
u
tp
u
t
y
,
wh
ich
is
ass
ig
n
ed
to
o
n
e
o
f
p
o
ten
tial
class
es.
T
h
e
L
L
M
aim
s
to
cr
ea
te
a
m
o
d
el
(
)
,
o
r
class
if
ier
,
u
s
in
g
a
t
r
ain
in
g
s
et
o
f
p
air
s
(
,
)
,
o
b
tain
e
d
f
r
o
m
p
r
io
r
o
b
s
er
v
atio
n
s
.
Fo
r
m
o
s
t
in
p
u
t p
atter
n
s
,
th
e
m
o
d
el
(
)
co
r
r
ec
tly
p
r
ed
icts
th
e
r
esp
o
n
s
e
=
(
)
.
W
h
en
co
n
s
id
er
in
g
elem
e
n
t
,
two
d
is
tin
ct
s
ce
n
ar
io
s
ar
is
e:
i
)
f
o
r
o
r
d
er
e
d
v
ar
iab
les,
v
ar
ies
wit
h
in
an
in
ter
v
al
[
,
]
o
n
th
e
r
ea
l
ax
is
,
with
a
n
ex
is
tin
g
o
r
d
er
in
g
r
elatio
n
s
h
ip
am
o
n
g
its
v
alu
es;
a
n
d
ii
)
f
o
r
n
o
m
in
al
(
ca
teg
o
r
ical)
v
a
r
iab
le
s
,
ca
n
o
n
ly
tak
e
v
alu
es
f
r
o
m
a
f
in
ite
s
et,
with
o
u
t
a
n
y
in
h
er
e
n
t
o
r
d
er
in
g
r
elatio
n
s
h
ip
.
T
h
e
L
L
M
g
en
e
r
a
tes
an
in
ter
p
r
etab
le
m
o
d
el
(
)
d
escr
ib
e
d
b
y
a
s
et
o
f
r
u
les
,
ex
p
r
ess
ed
in
if
-
t
h
en
f
o
r
m
:
if
<p
r
em
is
e>
th
en
<c
o
n
s
eq
u
en
ce
>
.
Fo
r
o
r
d
e
r
ed
v
ar
iab
le
1
in
th
e
d
o
m
ain
[
100
,
300
]
an
d
n
o
m
i
n
al
co
m
p
o
n
en
t
2
with
v
alu
es
{
,
,
}
,
a
p
o
s
s
ib
le
r
u
le
1
ca
n
b
e
ex
p
r
ess
ed
as f
o
llo
ws:
if
1
>
2000
AND
2
∈
{
,
}
th
en
=
0
wh
er
e
0
d
en
o
tes o
n
e
o
f
th
e
p
o
s
s
ib
le
ass
ig
n
m
en
ts
(
class
e
s
)
.
T
h
er
ef
o
r
e,
with
th
e
r
esu
lts
o
b
t
ain
ed
in
th
e
p
r
ev
io
u
s
s
tag
e,
′
an
d
′
=
{
1
,
0
}
,
th
e
class
co
n
d
itio
n
to
b
e
tak
en
is
th
e
class
th
at
ex
p
r
ess
es th
e
s
im
ilar
itie
s
o
f
-
s
eq
u
en
ce
s
in
p
o
s
itio
n
.
T
h
u
s
,
if
:
1
=
1
,
1
,
1
,
2
,
⋯
,
1
,
,
⋯
,
1
,
,
2
=
2
,
1
,
2
,
2
,
⋯
,
2
,
,
⋯
,
2
,
,
⋮
2
=
2
,
1
,
2
,
2
,
⋯
,
2
,
,
⋯
,
2
,
T
h
e
r
u
le
u
s
ed
is
th
at
if
1
,
≥
1
AN
D
2
,
≥
1
AND
3
,
≥
1
AND
⋯
AND
2
,
≥
1
th
en
=
1
,
wh
ich
ex
p
r
ess
es
th
e
m
in
im
u
m
co
m
p
lex
ity
o
f
t
h
e
lattice.
At
th
i
s
s
tag
e,
th
e
s
eq
u
en
ce
is
ex
p
r
ess
ed
in
th
e
f
o
r
m
=
{
1
,
2
⋯
,
⋯
,
}
with
=
{
0
,
1
}
,
s
o
th
er
e
ar
e
two
class
es
,
an
d
class
"1
"
ex
p
r
ess
es th
e
p
o
s
itio
n
th
at
is
d
eter
m
in
ed
as
th
e
co
n
s
er
v
ed
s
eq
u
en
ce
p
o
s
itio
n
.
I
n
th
e
p
r
io
r
p
r
o
ce
s
s
,
s
h
ad
o
w
clu
s
ter
in
g
o
cc
u
r
s
in
t
h
e
p
r
o
ce
s
s
[
4
1
]
,
an
d
with
th
e
in
p
u
t
b
ein
g
a
b
in
ar
y
s
eq
u
e
n
ce
in
th
is
s
tu
d
y
,
th
e
r
esu
lts
ca
n
b
e
d
ir
ec
tly
in
ter
p
r
ete
d
as in
tellig
ib
le
r
u
les.
2
.
1
.
6
.
P
ro
po
s
ed
co
ns
er
v
ed
s
equence
a
lg
o
rit
hm
T
h
e
alg
o
r
ith
m
f
o
r
d
eter
m
in
i
n
g
a
co
n
s
er
v
ed
s
eq
u
e
n
ce
is
s
h
o
wn
in
Alg
o
r
ith
m
2
,
wh
ich
co
m
b
in
es
p
r
o
g
r
ess
iv
e
alig
n
m
en
t
a
n
d
a
n
L
L
M
to
cr
ea
te
al
g
o
r
ith
m
.
T
o
d
eter
m
in
e
th
e
p
o
s
itio
n
o
f
c
o
n
s
er
v
ed
s
eq
u
en
ce
,
it
is
ass
u
m
e
d
th
at
′
is
u
n
b
r
o
k
en
1
-
v
alu
e
s
eq
u
en
ce
,
′
=
{
1
′
,
2
′
,
⋯
,
′
}
,
wh
er
e
′
⊂
,
1
′
≠
2
′
≠
⋯
≠
′
,
an
d
it
is
ass
u
m
ed
th
at
th
e
len
g
th
o
f
′
is
,
wh
er
e
1
<
<
.
T
h
u
s
,
th
e
co
n
s
er
v
ed
s
eq
u
en
ce
is
ex
p
r
ess
ed
as
′
with
th
e
m
ax
im
u
m
v
alu
e.
Alg
o
r
ith
m
2
.
C
o
n
s
er
v
ed
s
eq
u
e
n
ce
p
o
s
itio
n
inputs: Sequence
, number of sequences
output: Conserved sequence position
′
procedure
_
(
,
)
for
(
,
)
do
Align
and
using Needleman
-
Wunsch
(
,
)
;
Calculate Transition
,
=
∑
,
;
Calculate Transversion
,
=
∑
,
;
end
for
(
,
)
do
Construct guide tree
=
ℎ
_
(
,
)
;
Align sequences
′
=
_
(
,
)
;
=
ℎ
(
′
)
;
end
Construct temporary sequence
;
1
=
0
;
2
=
0
;
for
_
,
=
3
,
4
,
⋯
,
−
1
do
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2252
-
8
9
3
8
I
n
t J Ar
tif
I
n
tell
,
Vo
l.
15
,
No
.
4
,
Au
g
u
s
t 2
0
2
6
:
3
1
8
9
-
3
2
0
1
3194
=
(
−
2
)
+
−
1
;
end
for
(
′
,
)
do
for
′
,
=
1
,
2
,
⋯
,
−
1
do
for
′
,
=
+
1
,
+
2
,
⋯
,
do
for
,
=
1
,
2
,
⋯
,
do
if
,
′
=
,
′
then
(
−
1
)
(
−
1
)
+
(
−
)
−
,
=
1
;
else if
,
′
≠
,
′
then
(
−
1
)
(
−
1
)
+
(
−
)
−
,
=
0
;
end
end
end
end
lattice
=
T
,
=
1
,
2
,
⋯
,
2
;
end
Perform shadow clustering of
;
Select the minimum complexity of
as class
"
1"
;
Convert the minimum complexity into Intelligible rules;
for
do
Use intelligible rules to classify
;
Define class
"
1"
as a position of conserved sequence;
Transform class of
into binary sequence
=
{
1
,
2
,
⋯
,
}
;
end
find
′
⊂
unbroken sequence of
1
of
’
;
if length
′
is MAX then
′
conserved sequence position;
end
end
2
.
1
.
7
.
Cent
ra
l
do
g
m
a
T
h
e
ce
n
tr
al
d
o
g
m
a
o
f
m
o
lec
u
lar
b
io
lo
g
y
o
u
tlin
es
th
e
tr
an
s
f
o
r
m
atio
n
o
f
g
e
n
etic
in
f
o
r
m
atio
n
f
r
o
m
DNA
to
r
ib
o
n
u
cleic
ac
i
d
(
R
NA
)
an
d
s
u
b
s
eq
u
en
tl
y
to
p
r
o
tein
s
.
Du
r
in
g
tr
a
n
s
cr
ip
tio
n
,
th
e
n
u
cle
o
tid
e
b
ase
th
y
m
in
e
(
T
)
in
DNA
is
r
ep
la
ce
d
b
y
u
r
ac
il
(
U)
in
R
NA
[
4
2
]
.
A
m
o
r
e
co
m
p
le
x
p
r
o
ce
s
s
o
cc
u
r
s
d
u
r
in
g
th
e
tr
an
s
itio
n
f
r
o
m
R
NA
to
p
r
o
tei
n
.
T
h
e
c
h
an
g
e
to
a
p
r
o
tein
is
b
ased
o
n
co
d
o
n
s
c
o
m
p
o
s
ed
o
f
t
h
r
ee
b
ase
g
r
o
u
p
s
in
R
NA;
th
i
s
p
r
o
ce
s
s
is
ca
lled
t
r
an
s
latio
n
.
T
h
e
ce
n
tr
al
d
o
g
m
a
was
u
s
ed
to
co
n
v
er
t
co
n
s
er
v
ed
s
eq
u
en
ce
s
in
t
o
p
r
o
tein
s
f
o
r
f
u
r
t
h
er
an
al
y
s
is
.
2
.
2
.
I
mm
un
o
info
rma
t
ics
a
na
ly
s
is
I
m
m
u
n
o
in
f
o
r
m
atics
an
aly
s
is
was
u
s
ed
to
d
eter
m
in
e
th
e
lev
el
o
f
im
m
u
n
o
g
e
n
icity
,
o
r
th
e
a
b
ilit
y
o
f
an
an
tig
en
to
s
tim
u
late
th
e
f
o
r
m
atio
n
o
f
s
p
ec
if
ic
a
n
tib
o
d
ies
[
4
3
]
.
T
h
e
an
tib
o
d
ies
u
s
ed
a
r
e
ep
ito
p
e
-
s
p
ec
if
ic,
tar
g
etin
g
ce
r
tain
ar
ea
s
o
f
th
e
an
tig
en
ic
m
o
lecu
le
th
at
b
in
d
to
an
tib
o
d
ies
o
r
r
ec
ep
t
o
r
s
o
n
B
ce
lls
o
r
T
ce
lls
;
B
ce
lls
wer
e
u
s
ed
in
th
is
s
tu
d
y
.
B
ce
lls
o
r
B
ly
m
p
h
o
cy
te
s
p
lay
an
im
p
o
r
ta
n
t
r
o
le
in
h
u
m
o
r
al
im
m
u
n
ity
,
wh
er
ea
s
o
th
er
ly
m
p
h
o
c
y
tes,
n
am
ely
T
ce
lls
,
ar
e
cr
u
cial
in
c
ellu
lar
im
m
u
n
ity
.
T
h
e
m
ain
f
u
n
ctio
n
o
f
B
ce
lls
is
to
p
r
o
d
u
ce
an
tib
o
d
ies ag
ain
s
t
an
tig
en
s
.
T
o
d
eter
m
in
e
th
e
B
ce
ll e
p
ito
p
e,
th
e
f
o
llo
win
g
s
tep
s
wer
e
tak
en
:
i)
Sco
r
in
g
r
esid
u
es
co
n
tain
ed
in
th
e
p
r
o
tein
s
eq
u
en
ce
u
s
in
g
B
ep
iPre
d
2
.
0
;
th
e
s
co
r
e
o
b
tai
n
ed
f
r
o
m
th
e
p
r
o
tein
was d
eter
m
in
e
d
to
b
e
a
B
ce
ll e
p
ito
p
e
if
it h
ad
a
n
ep
i
to
p
e
s
co
r
e
≥
0
.
5
[
4
3
]
.
ii)
R
esid
u
es e
x
p
r
ess
ed
as e
p
ito
p
es in
u
n
b
r
o
k
en
p
r
o
tein
s
eq
u
en
c
es a
r
e
r
ef
er
r
e
d
to
as p
ep
tid
es
[
4
3
]
.
Sco
r
in
g
was
p
er
f
o
r
m
e
d
f
o
r
e
ac
h
p
ep
tid
e
s
eq
u
en
ce
u
s
in
g
Vax
i
J
en
v
2
.
0
.
Pep
tid
es
ar
e
d
ec
lar
ed
as
v
ac
cin
e
ca
n
d
id
ates if
th
e
p
e
p
tid
e
s
co
r
e
o
b
tain
ed
is
≥
0
.
4
[
4
4
]
.
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
o
ev
alu
ate
th
e
alg
o
r
ith
m
,
t
h
e
s
eq
u
en
ce
s
o
f
3
1
SAR
S
-
C
o
V
-
2
v
ar
ian
ts
wer
e
u
s
ed
,
as
s
h
o
wn
i
n
T
ab
le
1
.
T
h
e
d
ata
in
T
ab
le
1
wer
e
o
b
tain
ed
f
r
o
m
th
e
Natio
n
al
C
en
ter
f
o
r
B
io
tech
n
o
l
o
g
y
I
n
f
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T
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⋮
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31
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Dis
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Evaluation Warning : The document was created with Spire.PDF for Python.
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3
8
I
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tell
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,
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co
n
s
id
er
ed
ac
ce
p
tab
le
i
f
th
e
y
ar
e
im
m
u
n
o
g
e
n
s
,
n
o
n
-
to
x
in
s
,
an
d
n
o
n
-
aller
g
en
s
.
T
h
e
p
r
ed
ict
io
n
r
esu
lts
o
b
tain
ed
u
s
in
g
Aller
T
OP
an
d
T
o
x
i
n
Pre
d
ap
p
licatio
n
s
ar
e
lis
ted
in
T
ab
le
5
.
T
ab
le
5
s
h
o
ws
th
at
o
f
th
e
f
o
u
r
p
e
p
tid
es
p
r
ev
io
u
s
ly
o
b
tain
ed
,
o
n
ly
o
n
e
,
n
am
ely
Ptd
2
,
is
ac
ce
p
ted
as
an
in
s
ilico
v
ac
cin
e
ca
n
d
id
ate
b
ec
au
s
e
Ptd
2
is
an
im
m
u
n
o
g
en
,
n
o
n
-
aller
g
en
,
a
n
d
n
o
n
-
t
o
x
ic.
T
ab
le
5
.
Vac
cin
e
ca
n
d
id
ates statu
s
P
e
p
t
i
d
e
s
A
l
l
e
r
g
e
n
i
c
i
t
y
To
x
i
c
i
t
y
S
t
a
t
u
s
P
t
d
1
A
l
l
e
r
g
e
n
N
o
n
-
t
o
x
i
n
R
e
j
e
c
t
e
d
P
t
d
2
N
o
n
-
a
l
l
e
r
g
e
n
N
o
n
-
t
o
x
i
n
A
c
c
e
p
t
e
d
P
t
d
3
A
l
l
e
r
g
e
n
N
o
n
-
t
o
x
i
n
R
e
j
e
c
t
e
d
4.
CO
NCLU
SI
O
N
A
n
ex
p
er
im
en
t
o
n
a
h
y
b
r
id
al
g
o
r
ith
m
th
at
u
s
es
an
L
L
M
an
d
p
r
o
g
r
ess
iv
e
alig
n
m
en
t
was
p
r
esen
ted
,
f
r
o
m
w
h
ich
s
ev
er
al
co
n
clu
s
i
o
n
s
wer
e
d
r
awn
.
First,
th
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
d
em
o
n
s
tr
a
ted
its
ca
p
ab
ilit
y
to
id
en
tify
co
n
s
er
v
ed
s
eq
u
e
n
ce
s
.
E
m
p
lo
y
in
g
th
is
alg
o
r
ith
m
r
ev
ea
led
th
at
n
u
m
er
o
u
s
n
u
cleo
tid
e
m
u
tatio
n
s
,
p
ar
ticu
lar
ly
tr
an
s
itio
n
s
an
d
t
r
an
s
v
er
s
io
n
s
,
wer
e
ex
p
r
ess
ed
as
m
u
tatio
n
p
er
ce
n
tag
es,
in
d
icatin
g
th
at
th
e
m
u
tatio
n
r
ate
with
in
th
e
s
eq
u
en
ce
d
id
n
o
t
ex
ce
ed
1
.
5
%.
T
h
is
m
u
tatio
n
p
er
ce
n
tag
e
s
u
g
g
ests
h
o
m
o
lo
g
y
to
SAR
S
-
C
o
V
-
2
o
f
ap
p
r
o
x
im
ate
ly
±
9
8
.
5
%,
with
th
e
h
ig
h
est
m
u
tatio
n
p
er
ce
n
tag
e
in
th
e
t
h
eta
B
.
1
.
6
1
7
.
3
an
d
Om
icr
o
n
B
A.
1
v
ar
ian
ts
at
1
.
4
5
7
8
%,
an
d
th
e
lo
west
in
O
m
icr
o
n
B
A.
1
an
d
Om
icr
o
n
B
A.
1
.
1
at
0
.
0
0
6
7
%
.
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