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DATE 2016-10-01

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MESSAGE
DATE 2016-10-27
FROM Ruben Safir
SUBJECT Re: [Learn] Phylogenetics educational links
From learn-bounces-at-nylxs.com Thu Oct 27 23:08:57 2016
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From: Ruben Safir
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FWIW

https://www.youtube.com/watch?v=3D4FUr3_2tzOc

the future I think is in ctscans


On 10/27/2016 10:47 PM, Ruben Safir wrote:
> On 10/27/2016 04:09 PM, Christopher League wrote:
>>
>> Here's a set of introductory slides on inference of phylogenetic trees.
>>
>>
>>
>> Based on what I've learned today, "small" parsimony algorithms like
>> Fitch and Sankoff rely on labeling a *given* tree shape (aka topology),
>> so we already have to know (or hypothesize) the ancestral relationships.
>> The algorithm just determines which labels (mutations) to assign to
>> interior nodes. That's really unsatisfying to me.
>>
>> But the "big" parsimony techniques have to search the entire tree space,
>> which is ENORMOUS. The problem is formally NP-hard. Now -- people do
>> manage to solve (or approximately solve) NP-hard problems every day by
>> using piles of dirty tricks. When it comes to searching gigantic spaces,
>> those dirty tricks are the classic techniques of artificial
>> intelligence.
>>
>> So the lecture slides get into techniques like greedy algorithms,
>> hill-climbing, simulated annealing, genetic algorithms, etc. Anyway,
>> there could be a lot of meat here that fits under the heading of AI +
>> phylogenetics. It's much more accessible stuff than trying to
>> automatically interpret 3D model data to take measurements of maxillary
>> bones.
>>
>> CL
>>
>>
>> Ruben Safir writes:
>>
>>> http://telliott99.blogspot.com/2010/03/fitch-and-sankoff-algorithms-for=
.html
>>>
>>> "The Fitch algorithm considers the sites (or characters) one at a time.=
At each tip in the tree, we create a set containing those nucleotides (sta=
tes) that are observed or are compatible with the observation. Thus, if we =
see an A, we create the set {A}. If we see an ambiguity such as R, we creat=
e the set {AG}. Now we move down the tree [away from the tips]. In algorith=
mic terms, we do a postorder tree traversal. At each interior node we creat=
e a set that is the intersection of sets at the two descendant nodes. Howev=
er, if that set is empty, we instead create the set that is the union of th=
e two sets at the descendant nodes. Every time we create such a union, we a=
lso count one change of state."
>>>
>>>
>>> https://en.wikipedia.org/wiki/Non-parametric
>>> Nonparametric statistics are statistics not based on parameterized fami=
lies of probability distributions. They include both descriptive and infere=
ntial statistics. The typical parameters are the mean, variance, etc. Unlik=
e parametric statistics, nonparametric statistics make no assumptions about=
the probability distributions of the variables being assessed. The differe=
nce between parametric models and non-parametric models is that the former =
has a fixed number of parameters, while the latter grows the number of para=
meters with the amount of training data.[1] Note that the non-parametric mo=
del does, counterintuitively, contain parameters: the distinction is that p=
arameters are determined by the training data in the case of non-parametric=
statistics, not the model.
>>>
>>> https://en.wikipedia.org/wiki/Fitch-Margoliash_algorithm
>>> Distance-matrix methods
>>>
>>> Distance-matrix methods of phylogenetic analysis explicitly rely on a m=
easure of "genetic distance" between the sequences being classified, and th=
erefore they require an MSA (multiple sequence alignment) as an input. Dist=
ance is often defined as the fraction of mismatches at aligned positions, w=
ith gaps either ignored or counted as mismatches.[1] Distance methods attem=
pt to construct an all-to-all matrix from the sequence query set describing=
the distance between each sequence pair. From this is constructed a phylog=
enetic tree that places closely related sequences under the same interior n=
ode and whose branch lengths closely reproduce the observed distances betwe=
en sequences. Distance-matrix methods may produce either rooted or unrooted=
trees, depending on the algorithm used to calculate them. They are frequen=
tly used as the basis for progressive and iterative types of multiple seque=
nce alignment. The main disadvantage of distance-matrix methods is their in=
ability to efficiently use =

>>> information about local high-variation regions that appear across mult=
iple subtrees.[2]
>>>
>>>
>>> -- =

>>> So many immigrant groups have swept through our town
>>> that Brooklyn, like Atlantis, reaches mythological
>>> proportions in the mind of the world - RI Safir 1998
>>> http://www.mrbrklyn.com =

>>>
>>> DRM is THEFT - We are the STAKEHOLDERS - RI Safir 2002
>>> http://www.nylxs.com - Leadership Development in Free Software
>>> http://www2.mrbrklyn.com/resources - Unpublished Archive
>>> http://www.coinhangout.com - coins!
>>> http://www.brooklyn-living.com
>>>
>>> Being so tracked is for FARM ANIMALS and and extermination camps,
>>> but incompatible with living as a free human being. -RI Safir 2013
>>> _______________________________________________
>>> Learn mailing list
>>> Learn-at-nylxs.com
>>> http://lists.mrbrklyn.com/mailman/listinfo/learn
>>
>>
>>
>> _______________________________________________
>> Learn mailing list
>> Learn-at-nylxs.com
>> http://lists.mrbrklyn.com/mailman/listinfo/learn
>>
> =

> Since there are n OTUs to insert, the outer loop iterates n
> =E2=88=92
> 1 times.
> When there are n leaves in the tree, there are
> 2n
> =E2=88=92
> 1 places to insert the new OTU, and determining the cost of the result
> requires O(n)time. Thus, a greedy algorithm for inferring a phylogeny is
> O(n3).
> =

> =

> Any chance you can explain this better? How did it get the N cubed?
> I'm sick of not understanding this.
> =

> =



-- =

So many immigrant groups have swept through our town
that Brooklyn, like Atlantis, reaches mythological
proportions in the mind of the world - RI Safir 1998
http://www.mrbrklyn.com

DRM is THEFT - We are the STAKEHOLDERS - RI Safir 2002
http://www.nylxs.com - Leadership Development in Free Software
http://www2.mrbrklyn.com/resources - Unpublished Archive
http://www.coinhangout.com - coins!
http://www.brooklyn-living.com

Being so tracked is for FARM ANIMALS and and extermination camps,
but incompatible with living as a free human being. -RI Safir 2013
_______________________________________________
Learn mailing list
Learn-at-nylxs.com
http://lists.mrbrklyn.com/mailman/listinfo/learn

  1. 2016-10-04 ruben safir <ruben-at-mrbrklyn.com> Re: [Learn] Check List of Texts to learn Cladistics and
  2. 2016-10-04 Ruben Safir <ruben-at-mrbrklyn.com> Re: [Learn] Library access
  3. 2016-10-04 Ruben Safir <ruben-at-mrbrklyn.com> Re: [Learn] Library access
  4. 2016-10-04 Christopher League <christopher.league-at-liu.edu> Re: [Learn] phylogenetics
  5. 2016-10-04 Ruben Safir <ruben-at-mrbrklyn.com> Subject: [Learn] 3rd scans and displays for msueums
  6. 2016-10-04 Ruben Safir <ruben-at-mrbrklyn.com> Subject: [Learn] =?utf-8?q?Residual_diversity_estimates=E2=80=99_do_not_co?=
  7. 2016-10-04 Ruben Safir <ruben-at-mrbrklyn.com> Subject: [Learn] another paper on this topic to dig through
  8. 2016-10-04 Ruben Safir <ruben.safir-at-my.liu.edu> Subject: [Learn] Basic Phylogeny and Systematics
  9. 2016-10-04 Ruben Safir <ruben-at-mrbrklyn.com> Subject: [Learn] Library access
  10. 2016-10-05 Ruben Safir <mrbrklyn-at-panix.com> Re: [Learn] 3rd scans and displays for msueums
  11. 2016-10-05 ruben safir <ruben-at-mrbrklyn.com> Subject: [Learn] Fwd: Re: Check List of Texts to learn Cladistics and
  12. 2016-10-06 From: "Ruben.Safir" <ruben.safir-at-my.liu.edu> Subject: [Learn] TNT - Boom
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  14. 2016-10-09 ruben safir <ruben-at-mrbrklyn.com> Subject: [Learn] Fwd: phylogeny tyrannosauroid dinosaurs
  15. 2016-10-09 Ruben Safir <ruben-at-mrbrklyn.com> Subject: [Learn] Fwd: Re: phylogeny tyrannosauroid dinosaurs
  16. 2016-10-09 Ruben Safir <ruben-at-mrbrklyn.com> Subject: [Learn] Fwd: Re: [dinosaur] phylogeny tyrannosauroid dinosaurs
  17. 2016-10-10 Ruben Safir <ruben-at-mrbrklyn.com> Re: [Learn] Paleo meeting time
  18. 2016-10-10 Ruben Safir <ruben-at-mrbrklyn.com> Re: [Learn] phylogeny tyrannosauroid dinosaurs
  19. 2016-10-10 Steve Brusatte <brusatte-at-gmail.com> Re: [Learn] phylogeny tyrannosauroid dinosaurs
  20. 2016-10-10 Ruben Safir <ruben-at-mrbrklyn.com> Re: [Learn] phylogeny tyrannosauroid dinosaurs
  21. 2016-10-10 From: =?UTF-8?B?RGF2aWQgxIxlcm7DvQ==?= <david.cerny1-at-gmail.com> Re: [Learn] [dinosaur] phylogeny tyrannosauroid dinosaurs
  22. 2016-10-10 Ruben Safir <ruben-at-mrbrklyn.com> Re: [Learn] [dinosaur] phylogeny tyrannosauroid dinosaurs
  23. 2016-10-10 Ruben Safir <ruben-at-mrbrklyn.com> Re: [Learn] [dinosaur] phylogeny tyrannosauroid dinosaurs
  24. 2016-10-10 Dalton Meyer <paleonerd12-at-gmail.com> Re: [Learn] [dinosaur] phylogeny tyrannosauroid dinosaurs
  25. 2016-10-10 Ruben Safir <ruben-at-mrbrklyn.com> Subject: [Learn] AI research
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  27. 2016-10-10 Ruben Safir <ruben-at-mrbrklyn.com> Subject: [Learn] Fwd: Re: [dinosaur] phylogeny tyrannosauroid dinosaurs
  28. 2016-10-10 Ruben Safir <ruben-at-mrbrklyn.com> Subject: [Learn] http://palaeos.com/phylogeny/index.html
  29. 2016-10-10 Ruben Safir <ruben.safir-at-my.liu.edu> Subject: [Learn] maxillary fenestra and promaxillary fenestra
  30. 2016-10-10 Christopher League <league-at-contrapunctus.net> Subject: [Learn] Paleo meeting time
  31. 2016-10-10 Christopher League <league-at-contrapunctus.net> Subject: [Learn] Paleo meeting time
  32. 2016-10-10 Ruben Safir <ruben-at-mrbrklyn.com> Subject: [Learn] promaxillary fenestra
  33. 2016-10-13 Ruben Safir <ruben-at-mrbrklyn.com> Re: [Learn] Invitation: Phylogenetics project mtg -at- Thu 2016-10-13
  34. 2016-10-13 Ruben Safir <ruben-at-mrbrklyn.com> Re: [Learn] Library access
  35. 2016-10-13 ruben safir <ruben-at-mrbrklyn.com> Subject: [Learn] Fwd: access to the screen
  36. 2016-10-13 ruben safir <ruben-at-mrbrklyn.com> Subject: [Learn] Fwd: access to the screen
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  51. 2016-10-25 Ruben Safir <ruben-at-mrbrklyn.com> Subject: [Learn] Phylogenetics educational links
  52. 2016-10-27 Christopher League <league-at-contrapunctus.net> Re: [Learn] Phylogenetics educational links
  53. 2016-10-27 Ruben Safir <mrbrklyn-at-panix.com> Re: [Learn] Phylogenetics educational links
  54. 2016-10-27 Ruben Safir <mrbrklyn-at-panix.com> Re: [Learn] Phylogenetics educational links
  55. 2016-10-27 Ruben Safir <ruben-at-mrbrklyn.com> Re: [Learn] Phylogenetics educational links
  56. 2016-10-27 Ruben Safir <mrbrklyn-at-panix.com> Re: [Learn] Phylogenetics educational links
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