<s>
Computational	O
difficulties	O
and	O
philosophical	O
objections	O
had	O
prevented	O
the	O
widespread	O
adoption	O
of	O
the	O
Bayesian	O
approach	O
until	O
the	O
1990s	O
,	O
when	O
Markov	B-General_Concept
Chain	I-General_Concept
Monte	I-General_Concept
Carlo	I-General_Concept
(	O
MCMC	O
)	O
algorithms	O
revolutionized	O
Bayesian	O
computation	O
.	O
</s>
<s>
MCMC	B-General_Concept
methods	I-General_Concept
can	O
be	O
described	O
in	O
three	O
steps	O
:	O
first	O
using	O
a	O
stochastic	O
mechanism	O
a	O
new	O
state	O
for	O
the	O
Markov	O
chain	O
is	O
proposed	O
.	O
</s>
<s>
Some	O
of	O
the	O
most	O
common	O
algorithms	O
used	O
in	O
MCMC	B-General_Concept
methods	I-General_Concept
include	O
the	O
Metropolis	B-Algorithm
–	I-Algorithm
Hastings	I-Algorithm
algorithms	I-Algorithm
,	O
the	O
Metropolis-Coupling	O
MCMC	O
(	O
MC³	O
)	O
and	O
the	O
LOCAL	O
algorithm	O
of	O
Larget	O
and	O
Simon	O
.	O
</s>
<s>
One	O
of	O
the	O
most	O
common	O
MCMC	B-General_Concept
methods	I-General_Concept
used	O
is	O
the	O
Metropolis	B-Algorithm
–	I-Algorithm
Hastings	I-Algorithm
algorithm	I-Algorithm
,	O
a	O
modified	O
version	O
of	O
the	O
original	O
Metropolis	B-Algorithm
algorithm	I-Algorithm
.	O
</s>
<s>
The	O
Metropolis	B-Algorithm
algorithm	I-Algorithm
is	O
described	O
in	O
the	O
following	O
steps	O
:	O
</s>
<s>
The	O
aim	O
of	O
Metropolis-Hastings	B-Algorithm
algorithm	I-Algorithm
is	O
to	O
produce	O
a	O
collection	O
of	O
states	O
with	O
a	O
determined	O
distribution	O
until	O
the	O
Markov	O
process	O
reaches	O
a	O
stationary	O
distribution	O
.	O
</s>
<s>
Zangh	O
,	O
Huelsenbeck	O
,	O
Der	O
Mark	O
,	O
Ronquist	O
&	O
Teslenko	O
https://nbisweden.github.io/MrBayes/	O
BEAST	O
Bayesian	O
Evolutionary	O
Analysis	O
Sampling	O
Trees	O
Bayesian	O
inference	O
,	O
relaxed	O
molecular	O
clock	O
,	O
demographic	O
history	O
A	O
.	O
J	O
.	O
Drummond	O
,	O
A	O
.	O
Rambaut	O
&	O
M	O
.	O
A	O
.	O
Suchard	O
https://beast.community	O
BEAST	B-Application
2	I-Application
A	O
software	O
platform	O
for	O
Bayesian	O
evolutionary	O
analysis	O
Bayesian	O
inference	O
,	O
packages	O
,	O
multiple	O
models	O
R	O
Bouckaert	O
,	O
J	O
Heled	O
,	O
D	O
Kühnert	O
,	O
T	O
Vaughan	O
,	O
CH	O
Wu	O
,	O
D	O
Xie	O
,	O
MA	O
Suchard	O
,	O
A	O
Rambaut	O
,	O
AJ	O
Drummond	O
.	O
</s>
<s>
http://www.beast2.orgPhyloBayes	O
/	O
PhyloBayes	O
MPI	O
Bayesian	O
Monte	B-General_Concept
Carlo	I-General_Concept
Markov	I-General_Concept
Chain	I-General_Concept
(	O
MCMC	O
)	O
sampler	O
for	O
phylogenetic	O
reconstruction	O
.	O
</s>
<s>
Dewey	O
,	O
C	O
.	O
Ané	O
http://www.stat.wisc.edu/~ane/bucky/BATWING	O
Bayesian	O
Analysis	O
of	O
Trees	O
With	O
Internal	O
Node	O
Generation	O
Bayesian	O
inference	O
,	O
demographic	O
history	O
,	O
population	O
splits	O
I	O
.	O
J	O
.	O
Wilson	O
,	O
D	O
.	O
Weale	O
,	O
D.Balding	O
http://www.maths.abdn.ac.uk/˜ijw	O
Bayes	O
Phylogenies	O
Bayesian	O
inference	O
of	O
trees	O
using	O
Markov	B-General_Concept
Chain	I-General_Concept
Monte	I-General_Concept
Carlo	I-General_Concept
methods	I-General_Concept
Bayesian	O
inference	O
,	O
multiple	O
models	O
,	O
mixture	O
model	O
(	O
auto-partitioning	O
)	O
M	O
.	O
Pagel	O
,	O
A	O
.	O
Meade	O
http://www.evolution.rdg.ac.uk/BayesPhy.html	O
Armadillo	O
Workflow	O
Platform	O
Workflow	O
platform	O
dedicated	O
to	O
phylogenetic	O
and	O
general	O
bioinformatic	O
analysis	O
GUI	O
wrapper	O
around	O
MrBayes	O
E	O
.	O
Lord	O
,	O
M	O
.	O
Leclercq	O
,	O
A	O
.	O
Boc	O
,	O
A.B.	O
</s>
