<s>
Pseudo	B-Algorithm
amino	I-Algorithm
acid	I-Algorithm
composition	I-Algorithm
,	O
or	O
PseAAC	B-Algorithm
,	O
in	O
molecular	O
biology	O
,	O
was	O
originally	O
introduced	O
by	O
Kuo-Chen	O
Chou	O
in	O
2001	O
to	O
represent	O
protein	O
samples	O
for	O
improving	O
protein	B-Application
subcellular	I-Application
localization	I-Application
prediction	I-Application
and	O
membrane	O
protein	O
type	O
prediction	O
.	O
</s>
<s>
To	O
avoid	O
completely	O
losing	O
the	O
sequence-order	O
information	O
,	O
the	O
concept	O
of	O
PseAAC	B-Algorithm
(	O
pseudo	O
amino	O
acid	O
composition	O
)	O
was	O
proposed	O
.	O
</s>
<s>
In	O
contrast	O
with	O
the	O
conventional	O
amino	O
acid	O
composition	O
(	O
AAC	O
)	O
that	O
contains	O
20	O
components	O
with	O
each	O
reflecting	O
the	O
occurrence	O
frequency	O
for	O
one	O
of	O
the	O
20	O
native	O
amino	O
acids	O
in	O
a	O
protein	O
,	O
the	O
PseAAC	B-Algorithm
contains	O
a	O
set	O
of	O
greater	O
than	O
20	O
discrete	O
factors	O
,	O
where	O
the	O
first	O
20	O
represent	O
the	O
components	O
of	O
its	O
conventional	O
amino	O
acid	O
composition	O
while	O
the	O
additional	O
factors	O
incorporate	O
some	O
sequence-order	O
information	O
via	O
various	O
pseudo	O
components	O
.	O
</s>
<s>
Therefore	O
,	O
the	O
essence	O
of	O
PseAAC	B-Algorithm
is	O
that	O
on	O
one	O
hand	O
it	O
covers	O
the	O
AA	O
composition	O
,	O
but	O
on	O
the	O
other	O
hand	O
it	O
contains	O
the	O
information	O
beyond	O
the	O
AA	O
composition	O
and	O
hence	O
can	O
better	O
reflect	O
the	O
feature	O
of	O
a	O
protein	O
sequence	O
through	O
a	O
discrete	O
model	O
.	O
</s>
<s>
Meanwhile	O
,	O
various	O
modes	O
to	O
formulate	O
the	O
PseAAC	B-Algorithm
vector	O
have	O
also	O
been	O
developed	O
,	O
as	O
summarized	O
in	O
a	O
2009	O
review	O
article	O
.	O
</s>
<s>
Using	O
Eq.6	O
is	O
just	O
one	O
of	O
the	O
many	O
modes	O
for	O
deriving	O
the	O
correlation	O
factors	O
in	O
PseAAC	B-Algorithm
or	O
its	O
components	O
.	O
</s>
<s>
The	O
others	O
,	O
such	O
as	O
the	O
physicochemical	O
distance	O
mode	O
and	O
amphiphilic	O
pattern	O
mode	O
,	O
can	O
also	O
be	O
used	O
to	O
derive	O
different	O
types	O
of	O
PseAAC	B-Algorithm
,	O
as	O
summarized	O
in	O
a	O
2009	O
review	O
article	O
.	O
</s>
<s>
In	O
2011	O
,	O
the	O
formulation	O
of	O
PseAAC	B-Algorithm
(	O
Eq.3	O
)	O
was	O
extended	O
to	O
a	O
form	O
of	O
the	O
general	O
PseAAC	B-Algorithm
as	O
given	O
by	O
:	O
</s>
<s>
The	O
general	O
PseAAC	B-Algorithm
can	O
be	O
used	O
to	O
reflect	O
any	O
desired	O
features	O
according	O
to	O
the	O
targets	O
of	O
research	O
,	O
including	O
those	O
core	O
features	O
such	O
as	O
functional	O
domain	O
,	O
sequential	O
evolution	O
,	O
and	O
gene	O
ontology	O
to	O
improve	O
the	O
prediction	O
quality	O
for	O
the	O
subcellular	O
localization	O
of	O
proteins	O
.	O
</s>
