#bayesian phylogeny

[a-dinosaur-a-day]

Idk who "mrbeast" is in the slightest all I know is every time someone brings him up I briefly go "wait why are people talking about a bayesian inference phylogenetics program on tumblr" before I remember that it's mrBAYES, and that's not what people are talking about

[arminreindl]

Turnersuchus: First of the Sea Crocs

A big find for crocodile finds was revealed two days ago. Turnersuchus hingleyae (Hingley's and Turner's crocodile) is the oldest described and basalmost thalattosuchian described so far and is of great importance to slowly figuring out where thalattosuchians come from.

But lets start with a brief introduction to thalattosuchians. As the name already suggests, thalattosuchians are primarily known to have been marine animals (tho exceptions are known). thalattosuchians can broadly be split into two groups. The teleosauroids, which look somewhat similar to what one might call a normal crocodile, and the metriorhynchoids, which especially in the derived members could aptly be described as crocodile mermaids. Below an example of each, on the left Macrospondylus by Nikolay Zverkov and on the right a generalized metriorhynchid by Gabriel Ugueto.

Thalattosuchians such as these two groups, which are sister clades and not successive lineages (so they co-occured rather than one having evolved from the other), were incredibly successful during the Jurassic, evolving enormous forms such as Plesiosuchus, Dakosaurus and Machimosaurus. Their wild success held on throughout the Jurassic until they eventually went extinct in the early Cretaceous. But despite how common and whidespread they are, we don't actually have much of a clue where they come from. Thalattosuchians just kinda appear during the Toarcian and are already found across multiple continents with both groups established. To complicate matters, their position among crocodiles is also rather shaky. Three main hypothesis exist. One is that they are a sister group to crocodyliforms (Protosuchians, Notosuchians and Neosuchians), that they are basal mesoeucrocodylians or that they are Neosuchians related to Pholidosaurids (like Sarcosuchus) and Dyrosaurs.

This is where Turnersuchus comes in. Discovered in the  Charmouth Mudstone Formation of Dorset, England, this genus is known from the skeletal material belonging to the back of the head, mandible, parts of the forearms and shoulder girdle as well as neck, body and tail vertebrae all preserved in five blocks and a few isolated pieces of bone. From that we can already see general similarities to derived thalattosuchians and basic traits like narrow jaws and reduced forelimbs (tho not nearly as extreme as in metriorhynchids).

The first significant part about this discovery is its age. Turnersuchus is from the Pliensbachian stage of the Jurassic, so it predates any previously diagnostic thalattosuchians. Secondly is its position. As I said above, thalattosuchians are divided into teleosauroids and metriorhynchoids. But Turnersuchus is neither, with both phylogenetic analysis finding it to fall outside of these groups. Now in fairness this is not rock solid, as there is only a single trait excluding it from the derived groups in either analysis, so future works might shake things up. But as things are right now, it's the oldest named and basalmost member of the entire clade. On a sidenote at least the oldest part is bound to change, as the paper mentions a Moroccon teleosauroid currently in press that is even older.

All of this allows for two things. For one, by comparing Turnersuchus with the basal members of both teleosauroids and metriorhynchoids scientists were able to gather a list of traits that appear to be ancestral to the group. In addition, Turnersuchus also preserves some features that separate it from all other thalattosuchians that are also indicative of being an early member. Just as one example a specific part of the basioccipital thats associated with long skulls is poorly developed, which means that while slender the jaws weren't as long as in some later thalattosuchians. A Bayesian analysis was also conducted in an attempt to nail down when thalattosuchians evolved. Now depending on which phylogeny is used (one with thalattosuchians as non-crocodyliforms and another with them as mesoeucrocodylians) you get different times. The former would place their origin in the Norian stage of the Triassic, the later in the Sinemurian stage of the Jurassic. In light of the Moroccon material alluded to by the paper, it would appear that they likely split from other crocodylomorphs sometime in the late Triassic.

And finally to wrap this up let me share the press release artwork to finally give a face to all this information. Now if you've read my post about fossil crocs of 2022 you might already recognize the artist, as she's been on a real streak with illustrating fossil crocs. If you don't know her, I highly recommend checking out her work. I'm of course talking about Júlia d'Oliveira.

And yes, of course I got the Wikipedia page for it ready. Tho with work getting in the way when it was published I almost feared I'd be unable to get to it first.

[unhonestlymirror]

"An interesting article Language trees with sampled ancestors support a hybrid model for the origin of Indo-European languages ​​in one of the most highly cited and leading scientific journals Science, which was published yesterday!

It is an excellent example of modern humanitarian research on the origin of Indo-European languages. Bayesian analysis, probabilistic models, language phylogeny (!), involvement of paleogenetic data - and we have the most accurate answer to the question about which dissertations on philology were defended and spears were broken for two centuries.

Indo-European languages ​​turned out to be much older than previously thought - ~6120 years BC!"

How convenient for them me not having money to pay for the full article because:

What the hell.

Priscus of Panium with Excerpta de Legationibus and the first mentioned Ukrainian words goes f*ck himself, as I understand correctly.

Grand Dutchy of Lithuania documents go f*ck themselves too in this case.

[evoldir]

Fwd: Course: Online.Phylogenomics.Dec2-6

Begin forwarded message: > From: evoldir@evol.biology.mcmaster.ca > Subject: Course: Online.Phylogenomics.Dec2-6 > Date: 26 August 2024 at 05:12:14 BST > To: rdmpage@gmail.com > > > > Dear all, we are excited to announce our upcoming online Phylogenomics > course, taking place from December 2-6. > > In this course we will present theory and exercises to infer > time-calibrated phylogenies from multi-locus genome data sets while > accounting for confounding factors such as the identification of > orthologuous sequences that are suitable as phylogenetic markers, > the selection of appropriate models of sequence evolution, and the > detection of gene-tree discordance due to incomplete lineage sorting > and introgression. > > > Course Highlights: Course website: > (https://ift.tt/W9ewvma ) > Format: Online (12:00-18:00 Berlin time) Topics Covered: Phylogenetic > inference methods (Maximum Likelihood, Bayesian inference) Multispecies > Coalescent Model and gene flow analysis Divergence-time estimation > techniques Who Should Attend: This course is perfect for researchers, > PhD students, postdocs and researchers who plan to infer phylogenetic > relationships and divergence times from multilocus data, with little > or no prior experience. Basic knowledge of UNIX and command-line tools > is required. > > Why Attend? By the end of this course, you'll have the skills to > accurately infer time-calibrated phylogenies from genome-scale data, > addressing key challenges like gene-tree discordance and model selection. > > For the full list of our courses and workshops, please visit: > (https://ift.tt/W9ewvma) > > Best regards, Carlo > > > Carlo Pecoraro, Ph.D > Physalia-courses DIRECTOR > info@physalia-courses.org > mobile: +49 17645230846 > > > > "info@physalia-courses.org"

[rnomics]

Insects, Vol. 15, Pages 371: A New Species of Scymnus (Coleoptera, Coccinellidae) from Pakistan with Mitochondrial Genome and Its Phylogenetic Implications

In this study, a new species of the subgenus Pullus belonging to the Scymnus genus from Pakistan, Scymnus (Pullus) cardi sp. nov., was described and illustrated, with information on its distribution, host plants, and prey. Additionally, the completed mitochondrial genome (mitogenome) of the new species using high-throughput sequencing technology was obtained. The genome contains the typical 37 genes (13 protein-coding genes, two ribosomal #RNAs, and 22 transfer #RNAs) and a non-coding control region, and is arranged in the same order as that of the putative ancestor of beetles. The AT content of the mitogenome is approximately 85.1%, with AT skew and GC skew of 0.05 and −0.43, respectively. The calculated values of relative synonymous codon usage (RSCU) determine that the codon UUA (L) has the highest frequency. Furthermore, we explored the phylogenetic relationship among 59 representatives of the Coccinellidae using Bayesian inference and maximum likelihood methods, the results of which strongly support the monophyly of Coccinellinae. The phylogenetic results positioned Scymnus (Pullus) cardi in a well-supported clade with Scymnus (Pullus) loewii and Scymnus (Pullus) rubricaudus within the genus Scymnus and the tribe Scymnini. The mitochondrial sequence of S. (P.) cardi will contribute to the mitochondrial genome database and provide helpful information for the identification and phylogeny of Coccinellidae. https://www.mdpi.com/2075-4450/15/5/371?utm_source=dlvr.it&utm_medium=tumblr

[typhlonectes]

Tetrapodophis amplectus is not a snake: re-assessment of the osteology, phylogeny and functional morphology of an Early Cretaceous dolichosaurid lizard

Caldwell et al.

Abstract

The origin of snakes remains one of the most contentious evolutionary transitions in vertebrate evolution. The discovery of snake fossils with well-formed hind limbs provided new insights into the phylogenetic and ecological origin of snakes. 

In 2015, a fossil from the Early Cretaceous Crato Formation of Brazil was described as the first known snake with fore- and hind limbs (Tetrapodophis amplectus), and was proposed to be fossorial, to exhibit large gape feeding adaptations (macrostomy) and to possess morphologies suggesting constriction behaviours. 

First-hand examination of T. amplectus, including its undescribed counterpart, provides new evidence refuting it as a snake. 

We find: a long rostrum; straight mandible; teeth not hooked zygosphenes/zygantra absent; neural arch and spines present and tall with apical epiphyses; rib heads not tubercular; synapophyses simple; and lymphapophyses absent. Claimed traits not preserved include: braincase/descensus parietalis; ‘L’-shaped nasals; intramandibular joint; replacement tooth crowns; haemal keels; tracheal rings; and large ventral scales. 

New observations include: elongate retroarticular process; apex of splenial terminating below posterior extent of tooth row; >10 cervicals with hypapophyses and articulating intercentra; haemapophyses with articulating arches; reduced articular surfaces on appendicular elements; rows of small body scales; and reduced mesopodial ossification. The axial skeleton is uniquely elongate and the tail with >100 vertebrae is not short as previously claimed, although overall the animal is small (∼195 mm total length). We assessed the relationships of Tetrapodophis using a revised version of the original morphological dataset, an independent morphological dataset, and these two datasets combined with molecular data. All four were analysed under parsimony and Bayesian inference and unambiguously recover Tetrapodophis as a dolichosaur. 

We find that Tetrapodophis shows aquatic adaptations and there is no evidence to support constricting behaviour or macrostomy.

Read the paper here: 

https://www.tandfonline.com/doi/full/10.1080/14772019.2021.1983044

[sciencespies]

Move over, Neanderthals. This could actually be our closest human relative

https://sciencespies.com/humans/move-over-neanderthals-this-could-actually-be-our-closest-human-relative/

Move over, Neanderthals. This could actually be our closest human relative

In 1933 a mysterious fossil skull was discovered near Harbin City in the Heilongjiang province of north-eastern China. Despite being nearly perfectly preserved – with square eye sockets, thick brow ridges and large teeth – nobody could work out exactly what it was.

The skull is much bigger than that of Homo sapiens and other human species – and its brain size is similar to that of our own species. Historical events left it without a secure place of origin or date, until today.

Now a team of Chinese, Australian and British researchers has finally solved the puzzle – the skull represents a previously unknown extinct human species. The research, published as three studies in the journal Innovation, suggests this is our closest relative in the human family tree.

Dubbed Homo longi, which can be translated as “dragon river”, it is named after the province in which it was found. The identification of the skull, thought to have come from a 50-year-old male, was partly based on chemical analysis of sediments trapped inside it.

This confirmed it comes from the upper part of the Huangshan rock formation near Harbin City. The formation was reliably dated to the Middle Pleistocene – 125,000 to 800,000 years ago. Uranium series dating, which involves using the known rate of decay of radioactive uranium atoms in a sample to work out its age, showed that the fossil itself is at least 146,000 years old.

Homo longi can now takes its place among an ever increasing number of hominin species across Africa, Europe and Asia.

Fossil human skulls H. erectus (left) and H. longi (furthest right). (Kai Geng)

Constructing a family tree

Determining the historical relationship between fossil species, however, remains one of the most difficult tasks in the study of human evolution.

In recent years, the analysis of ancient DNA has transformed our understanding of the relationship between early populations of modern humans. It has also highlighted how we are different – and similar – to our most immediate relatives, the Neanderthals.

Surviving DNA, however, is very rare for fossil hominins from the Middle Pleistocene, as it tends to degrade over time. Evolutionary relationships must therefore be determined using other evidence. This is usually data on the shape – morphology – of fossils, their age and geographical location.

The Harbin team generated a family tree (“phylogeny”) of human lineages to work out how the species relates to modern humans. This tree is based on morphological data from 95 largely complete fossil specimens of different hominin species living during the Middle Pleistocene, including Homo erectus, Homo neanderthalensis, Homo heidelbergensis and Homo sapiens along with their known ages.

The tree also suggests that five previously unidentified fossils from northeastern China are from Homo longi.

Human family tree. (Ni et al. Innovation, 2021)

It predicts that the common ancestor of Homo longi and Homo sapiens lived approximately 950,000 years ago. Furthermore, it suggests that both species shared a common ancestor with Neanderthals a bit more than 1 million years ago, meaning we may have split from Neanderthals 400,000 earlier than previously thought (we used to think it was 600,000 years ago).

Until now, the Neanderthals were considered our closest relative (according to the study, we split from Homo heidelbergensis some 1.3 million years ago). Debates about the evolution of modern humans and what it is that makes us “human” therefore relied heavily on comparisons to Neanderthals.

But the new discovery pushes Neanderthals one step further away from ourselves and makes simple comparisons between two species much less important to understanding what ultimately makes us who we are.

There are, however, still significant points of concern about the dating of this phylogenetic model, as recognized by the authors. The predicted dates for the common ancestors between human lineages do not match the dates of actual discovered fossils, or those predicted by the analysis of DNA.

For example, this study proposes that there was Homo sapiens in Eurasia at about 400,000 years ago. But the oldest fossil for this species known outside Africa is little more than half this age.

At the same time, the split between Homo sapiens and Neanderthals predicted here at more than 1 million years old does not match the prediction of nuclear DNA analysis, which suggests it happened much later. However, it can be backed up by doing DNA analysis with genetic material taken from the cell’s engine, called the mitochondria.

The older estimates presented by this study may result from the use of new techniques, called Bayesian tip dating, which aren’t normally used in evolutionary studies. These can take into account both morphological and molecular data and make predictions about the possible sequence and date of the divergence of species.

Reconstruction of Homo longi. (Chuang Zhao)

Wider perspective

While the shape of the family tree presented here is likely to stand the test of time, it is still too early to accept these predicted divergence dates as definitive. That said, the research also sheds important light on how human species occurred and spread through the Middle Pleistocene – into all areas of our planet. Crucially, many of these species may have interbreed.

Europe was the origin point for Neanderthals. Meanwhile, the Asian human species Homo erectus was a critical evolutionary step, giving rise to all later hominin species. And now we know that Homo longi evolved in Asia too. It therefore looks like Africa was a destination as well as a point of origin for the spread of human species.

The Harbin cranium also tells another story about human evolution as a science and as an international discipline. Human evolution was originally a European area of interest, focused on evidence from sites in western and central Europe. The discovery of fossils in Africa added great time depth to the origins of the human lineage and led to a common story of the spread of new species out of Africa.

The Harbin cranium reminds us of the vast expanse of Asia, whose fossils and scientists are now coming to the fore. Further insights may come both from the discovery of new species and old figurative art.

In the case of the Harbin cranium, it is the application of new techniques of analysis that has brought old specimens back into active use. Asia is now in the driving seat of the study of human evolution.

Anthony Sinclair, Professor of Archaeological Theory and Method, University of Liverpool.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

#Humans

[apocalyptic-antics]

CHARACTER ANALYSIS

CHARACTER STEP MATRIX

As reviewed earlier, assigning a character state transformation determines  the  number  of  steps  that  may  occur  when  going  from one character state to another. Computerized phylogeny reconstruction algorithms available today permit a more precise tabulation of the number of steps occurring between each pair of character states through a character step matrix. The matrix consists of a listing of character states in a top row and left  column;  intersecting  numbers  within  the  matrix  indicate  the  number  of  steps  required,  going  from  states  in  the  left  column  to  states  in  the  top  row.  For  example,  the  character  step  matrix  of  Figure  2.5A  illustrates  an  ordered  character  state transformation series, such that a single step is required when going from state 0 to state 1 (or state 1 to state 0), two steps are required when going from state 0 to state 2, etc. The character  step  matrix  of  Figure  2.5B  shows  an  unordered  transformation series, in which a single step is required when going   from   one   state   to   any   other   (nonidentical)  state.   Character  step  matrices  need  not  be  symmetrical;  that  of  Figure  2.5C  illustrates  an  ordered  transformation  series  but  one  that  is  irreversible,  disallowing  a  change  from  a  higher  state number to a lower state number (e.g., from state 2 to state 1) by requiring a large number of step changes (symbolized by “∞”). Character step matrices are most useful with specialized types  of  data.  For  example,  the  matrix  of  Figure  2.5D  could represent DNA sequence data, where 0 and 1 are the states for the  two purines  (adenine  and  guanine)  and  2  and  3  are  the  states  for  the  two pyrimidines  (cytosine  and  thymine;  see  Chapter  14).  Note  that  in  this matrix  the  change  from  one  purine to another purine or one pyrimidine to another pyrimidine (each of these known as a “transition”) requires only one step, being  biochemically more probable to occur, whereas a change from a purine to a pyrimidine or from a pyrimidine to a  purine  (termed  a “transversion”)  is  given  five  steps,  being  more  biochemically  less  likely. Thus,  in  a  cladistic  analysis,  the latter change will be given substantially more weight.

DNA sequence data may be transformed in a more complicated evolutionary model, based on a number of parameters, such  as  branch  length,  codon position,  base  frequency,  or  transition/transversion ratio. Such models of evolution are an integral  component  of  maximum  likelihood  and  Bayesian analyses (see later discussion).

Chapter Two  Plant Systematics Second Edition Michael G. Simpson

[albertonykus]

What software do you use to make cladograms?

That depends on which cladograms you’re asking about. For something quick and simple like the one below, I use a specialized software called TreeGraph.

For the time-scaled bird phylogenies I posted a while back, I used... Microsoft PowerPoint, believe it or not. (There are also packages in R that can make similar graphics.)

For the Cartoon Guide to Vertebrate Evolution? Hand drawn in GIMP using a drawing tablet (like most of my drawings).

For running actual phylogenetic analyses in my research? TNT (for parsimony) and MrBayes (for Bayesian methods).

[saurian-game]

Saurian DevLog #47

Hey all,

We've been working really hard on getting the next patch out, as well as the art book so all of the team is in ultra-busy mode at the moment. Henry has some information for you on what is to come with regards to the patch and I thought I'd drop some science seeing as an interesting new paper just dropped that we got a first-look at.

Henry

The programming team has been busy working out the last bugs from the gradual ontogeny system implementation, as well as some other longer-standing ones. After some last-minute sprints, we're happy to say it's ready! Patch notes can be found here - please let us know if you encounter any issues. Otherwise, enjoy!

Tom

A bit ago we were contacted by palaeontologist Mike Lee, asking if they could use our Thoracosaurus render in the press release of a new paper he had in the works featuring this animal. Always happy to have our art used for sci-comm, we said yes and Mike was kind enough to send us a pre-print of the paper in question. It turned out to be a pretty cool study, and had some implications for us which I thought would be interesting to discuss. Seeing as it has now been published I thought I'd talk about it here today.

To be clear, it won't effect how the animal will appear in game, but I did have to re-write the profiles for all our crocodylomorphs in the art book and I will have to modify the encyclopedia entries as well.

Thoracosaurus is a genus of large (5m or more) marine crocodylomorph from the late cretaceous of North America (including Hell Creek) and Europe. Since it was first discovered, Thoracosaurus has been considered an early member of the gharial lineage, with many similar aspects of the skeleton indicating this might have been the case. Computational phylogenetic analysis - computer run analysis that hypothesise the relationships of organisms - also consistently came to the same conclusion.

Borealosuchus is another crocodylomorph from Hell Creek that sometimes comes out as close to gharials, and sometimes in other positions close to the base of living crocodilians.

Traditional morphological studies had found gharials to be the earliest branching group of crocodylians. This was consistent with the 72 million year age of the earliest species of Thoracosaurus. however, new relationships and divergent dates received from molecular studies did not, with gharials being a reletively young group (40 Ma) more closely related to crocodiles than alligators. In this scenario, Thoracosaurus appears far before when gharials are supposed to have diverged from crocodiles.

This is where the new study by Mike Lee and his colleague Adam Yates comes in. They found that when running extremely complete phylogenies taking molecular, morphological and fossil age data into account, this disparity was resolved.

The inclusion of data related to age gaps between groups (tip-dating methodology) proved to be the difference, as without these methods the relationships came out similar to previous studies. The inclusion of tip-dating Bayesian approaches found Thoracosaurus and Borealosuchus to not be related to gharials at all, but out side of crocodylia. The position of gharials here agrees with molecular approaches, being young and close to crocodiles. This means than the gharial-like features of Thoracosaurus are all convergently evolved, probably as adaptions for catching fish.

So what does this mean for us, on a surface level? Well probably not a lot in terms of appearance, behaviour and ecology. What it does mean is than both Thoracosaurus and Borealosuchus are no longer crocodylians! They are stem-crocodylians and each other's closest reletives. So our crocodylian count in Saurian has dropped from 3 to 1, with early alligatoroid Brachychampsa being the only one left.

[perfectlytinyworkspace]

Phylogenetics

» motivation

goal: build a tree that gives us the evolutionary history of genomes, beyond simple sequence alignment similarities

before the advent of DNA sequencing, phylogenetic tree-building relied on phenotype

[often, this missed the distinction between true evolutionary similarity and convergent evolution]

why do we need the evolutionary history of organisms?

to trace pathogen evolution and pre-empt/treat pathologies

to measure and maintain biodiversity

to analyze/understand more about the evolution of a specific protein function in biochemistry research

i.e, ancestral sequence reconstruction of closely related specifically-binding proteins that possibly had a nonspecific common ancestor

» phylogenetic trees

rooted trees [centered around a selected LUCA] and unrooted trees, in either vertical or horizontal direction

axis perpendicular has no meaning

axis parallel to the branches may have meaning depending on cladogram (none) | chronogram (time) | phylogram (change/differences/number of mutations between)

dated, resolved bifurcated nodes [branches into 2 lines at every split] or undated, unresolved multifurcated nodes

internal branch and external branch – older and more recent branches

the individual species taxa and the clusters of related species in clades

» phylogeny algorithms

[scoring algorithms] best tree among the ones you've selected

parsimony:

generate unrooted tree models for different mutations

count the number of changes required between different branches

least changes = best tree, assuming mutations are all equally likely

issue w/ OG: not all mutations are equally likely, so in reality changes would have to be weighted

transitions are more likely than transversions due to nucleotide bases' chemical similarities

G's are most easily oxidized, which gives it a higher likelihood of mutating

organisms as a whole have differing baseline nucleotide preferences [GCAT proportions & codon preferences vary, so evolutionary pressures shift in one way or another]

modified/weighted parsimony

use maximum likelihood that makes the given data the most likely: likelihood L(d) = P(Data | H tree + evolutionary model) » L(d) = P(Data | H)

use Bayesian approach based on Bayes formula: P (tree T & evolutionary parameters ø) = [P(T, ø) • P(data D | T, ø)] / P(D)

for Bayes, you don't need to choose models to test, you can simply heuristically sample a few of them » this gives a probability distribution across different T's and ø's

[searching algorithms] selecting trees to be scored in the first place

# of unrooted bifurcating trees available: B(T) = ∏(2n – 5) with n = 3, creating an exponential function

finding ALL the trees is not feasible as the calculation becomes intensive

instead, use a heuristic algorithm to quickly find an alright (but not optimal) solution

bootstrapping to optimize: build a tree from a random subset of sequences with replacement

do this multiple times and note the trees that keep repeatedly being created as the more optimal ones

look at all the trees you've generated and see which % of them form certain branches

(i.e., 100% of trees agreeing on a branch means that the branch likely actually exists!)

phylogeny applications

for a universal Tree of Life™

a nice gene to use: ribosome small subunit that is needed for translation, which has both fast and slow-evolving regions

add in some ribosomal proteins to make the tree more accurate

are eukaryotes a smaller branch of archaea, or is there an equal eukarya/archaea branching with a split off from bacteria?

lateral gene transfer really makes things difficult

tracing epidemics

phylogenetics methods are useful for tracing flu/COVID epidemics & HIV

HIV phylogeny in criminal courses cases » victim & patient strain similarity via multiple scoring & tree-building methods for accuracy

covid-specific phylogeny – pangolin's con_lineages.org that lists all the mutations and keeps track of the COVID tree

[abuncolwild]

Descargar windows 7 mega 32 bits 無料ダウンロード.Download .NET Framework

Descargar windows 7 mega 32 bits 無料ダウンロード.MEGA - パソコン用

                                                                          The Latest Version:.ダウンロード Windows 7 Home Premium 32 bits 用 Windows 無料 |

    MEGA for Windows and Linux(32 and 64 bit) and macOS is now available. This is a bug fix release and is the current stable release Free for 32 bit win download. Development Tools downloads - MEGA by Tamura K, Peterson D, Peterson N, Stecher G, Nei M, and Kumar S and many more programs are available for instant and free download  · Downloads for building and running applications Framework. Get web installer, offline installer, and language pack downloads Framework    

Descargar windows 7 mega 32 bits 無料ダウンロード.Download ClocX - freeware analog clock

Free for 32 bit win download. Development Tools downloads - MEGA by Tamura K, Peterson D, Peterson N, Stecher G, Nei M, and Kumar S and many more programs are available for instant and free download  · Windows PCにMEGA をダウンロードしてインストールします。 あなたのコンピュータにMEGAをこのポストから無料でダウンロードしてインストールすることができます。PC上でMEGAを使うこの方法は、Windows 7/8 / / 10とすべてのMac OSで動作します。 These are ISO images created with ImgBurn from clean Windows 7 Professional SP1 install disks (32 bit and 64 bit respectively). These ISOs are English by default. Hopefully these are of use to someone who wishes to create virtual machines, or even install on older hardware!User Interaction Count: 73K         

 Version 11 adds new timing methods and is optimized for working with larger data. Calibration densities, tip dating, and a rate auto-correlation test have been added to MEGA.

The Maximum Likelihood system has been optimized for memory efficiency in version The Tree Explorer toolbar has been updated to be more intuitive and accessible. In the past 25 years, the MEGA software has been downloaded more then 2. Sophisticated and user-friendly software suite for analyzing DNA and protein sequence data from species and populations. MEGA This is a bug fix release and is the current stable release.

MEGA Molecular Evolutionary Genetics Analysis version 11 Version 11 adds new timing methods and is optimized for working with larger data. MEGA 11 introduces expanded relaxed-clock dating methods Calibration densities, tip dating, and a rate auto-correlation test have been added to MEGA. Memory efficiency of the ML system has been improved The Maximum Likelihood system has been optimized for memory efficiency in version Redesigned Tree Explorer toolbar The Tree Explorer toolbar has been updated to be more intuitive and accessible.

MEGA Software Celebrates Silver Anniversary In the past 25 years, the MEGA software has been downloaded more then 2. Instructional Videos Now Available Learn how to use MEGA from video tutorials created by MEGA users. Sequence Analyses Phylogeny Inference Model Selection Dating and Clocks Ancestral States Selection and Tests Sequence Alignment. Statistical Methods Maximum Likelihood Distance Methods Ordinary Least Squares Maximum Parsimony Composite Likelihood Bayesian.

Documentation Online Manual MEGA 1.

[evoldir]

Fwd: Course: Online.IntroSpatialEcoPhylogenetics.Mar19-22

Begin forwarded message: > From: evoldir@evol.biology.mcmaster.ca > Subject: Course: Online.IntroSpatialEcoPhylogenetics.Mar19-22 > Date: 29 February 2024 at 05:12:08 GMT > To: rdmpage@gmail.com > > > > ONLINE COURSE – An Introduction to Spatial Eco-Phylogenetics and > Comparative Methods (SECM01) > > We still have a few places available. > > https://ift.tt/z5yNXYf > > 19th - 22nd March 2024 > > Please feel free to share! > > COURSE OVERVIEW - > In this course we introduce phylogenetic analyses in a spatial > context. Phylogenetic analyses often imply a high number of species for > which phylogenetic information is unavailable, hence we begin by providing > an overview on modern techniques to incorporate phylogenetic uncertainty > in the analyses (day 1). We then cover the most popular analyses in the > spatial phylogenetics discipline (day 2), with particular focus on the > canonical analysis of neo- and paleo-endemism (CANAPE). The second part > of the course will be devoted to integrating phylogenetic information > into models of geographic distribution of species (day 3), followed by > an overview of recent advances to improve ecological forecasts using > phylogenetic mixed models in a Bayesian framework (day 4). > > By the end of the course, participants should: > > Know how to expand incomplete phylogenies based on taxonomic information > and customizing simulation parameters for optimal expansion. > Understand the metrics and concepts used in spatial phylogenetics > (i.e. phylogenetic alpha and beta diversity, phylogenetic endemism), > interpret them critically, and assess pros and cons of analytical > techniques.  Calculate phylogenetic predictors that can be included > as covariates in Species Distribution or Niche Models.  Understand and > implement the phylogenetic mixed model (PMM) and translate its predictions > into a spatial context. > > Day > 1 – Expansion of molecular trees using taxonomic information and > fundamental metrics of phylogenetic structure > > Software for tree expansion exercises; randtip, PhyloMaker > An overview of the fundamental metrics of phylogenetic structure. Null > models. > > Day > 2 – Spatial Phylogenetics > > Canonical analysis of neo- and paleo- endemism. Metrics, rationale, > workflow, and implementation. > > Day > 3 – Phylogenetic Species Distribution Models > > Putting phylogenies in the geography: the imprints of evolutionary > relationships in distribution models.  Combining phylogenies with > co-occurrence to infer spatial phylogenetic predictors.  Fitting, > evaluating and interpreting Phylogenetic-SDMs. > > Day > 4 – Beyond PGLS – Bayes and more > > Most common phylogenetic modelling approaches: PGLS PGLMM > The phylogenetic mixed model (PMM) in a Bayesian framework Please > email oliverhooker@prstatiatics.com with any questions. > > -- > > Oliver Hooker PhD. > PR stats > > Oliver Hooker

[geneticdrifting]

@whereofonecannotspeak I can answer this! Normally when we're talking about "relatedness" in this context, we're talking about divergence times. Now, there are ways to quantitatively estimate genetic relatedness - if you're curious you can look up fixation index (Fst). Fst compares variation within a population to variation between populations, using the frequency of nucleotides (A, T, C, and G) at shared sites. For example, if my "forest population" of a particular bird has all A's at a certain site, and my "field population" has all T's, the Fst at that site is 1. If both populations have all T's, the Fst is 0. If the forest population has mostly A's and the field population has mostly T's, the Fst is a little less than 1. You can scale this up across many sites (and many populations) in the genome to get an idea of relatedness.

However, this isn't super useful for looking at different species, since it doesn't tell us HOW they are related. There are also statistical issues with Fst as your organisms become more distantly related. Instead, we use phylogenies (essentially family trees):

When we're looking at a phylogeny, we can say that cows (bovids) and whales (cetaceans) are more closely related to each other than to horses, since they shared a more recent common ancestor. You can construct phylogenies by taking sequence data from one species and comparing it to another, via a sequence evolution model. You can use a single conserved gene, a collection of conserved genes, or even genome-wide shared sites, which you align together. Methods to generate phylogenies are getting very sophisticated, with a lot of people using Bayesian methods nowadays.

That rabbit/hare post is messing me up. I’d thought they were synonyms. Their development and social behavior are all different. They can’t even interbreed. They don’t have the same number of chromosomes. Dogs, wolves, jackals, and coyotes can mate with each other and have fertile offspring but rabbits and hares cant even make infertile ones bc they just die in the womb. Wack.

[supercunninglinguist]

Recent Perusals

Citations are in Harvard format:

Asano, M., Khrennikov, A., Ohya, M., Tanaka, Y. and Yamato, I., 2015. Quantum adaptivity in biology: from genetics to cognition. Heidelberg: Springer.

“The aim of this book is to introduce a theoretical/conceptual principle (based on quantum information theory and non-Kolmogorov probability theory) to understand information processing phenomena in biology as a whole — the information biology — a new research field, which is based on the application of open quantum systems (and, more generally, adaptive dynamics [173, 26, 175]) outside of physics as a powerful tool. Thus this book is about information processing performed by biosystems.“ (P. XI)

Radder, H. ed., 2003. The philosophy of scientific experimentation. University of Pittsburgh Press.

“Until the advent of computers, the primary tool physicists had at their disposal for representing their theoretical understanding of the mechanics and dynamics of material systems had been the differential equation, and their principal task was to relate the solutions of these equations to observed experimental effects. But differential equations are notoriously difficult to solve once they depart from the linear domain, and especially so when representing the interactions of many bodies. Thus, prior to the computer, the study of complex, nonlinear phenomena by physicists had been limited [...]” (Chapter 10, P. 200-201)

Blackmore, S., 1999. The meme machine—With a foreword of Richard Dawkins. 

“I like to ask a simple question – indeed I shall use this question again in several different contexts. Imagine a world full of hosts for memes (e.g. brains) and far more memes than can possibly find homes. Now ask, which memes are more likely to find a safe home and get passed on again? This is a reasonable way to characterise the real world we live in. Each of us creates or comes across countless memes every day. Most of our thoughts are potentially memes but if they do not get spoken they die out straight away. We produce memes every time we speak, but most of these are quickly snuffed out in their travels.” (P. 37)

Krantz, D., Luce, D., Suppes, P. and Tversky, A., 1971. Foundations of measurement, Vol. I: Additive and polynomial representations.

“Little seems possible in the way of a careful analysis of an attribute until means are devised to say which of two objects or events exhibits more of the attribute. Once we are able to order the objects in an acceptable way, we need to examine them for add itional structure, for example, by selecting two or more factors that affect the ordering. Then begins the search for qualitative laws satisfied by the ordering and the additional structure. In contrast to fundamental physical measurement, which is typically oned imensional (see, however, Chapter I O), many of the theories of measurement that appear applicable to behavioral problems are inherently multidi mensional, and so the measurement theories deal simultaneously with several measures and the laws connecting them.” (P. 32)

Jäger, G. and List, J.M., 2016. Statistical and computational elaborations of the classical comparative method.

“According to the subjective or Bayesian interpretation, the probability of an outcome quantifies the degree of certainty one has about this outcome. If, for instance, an election forecast says that candidate X has a 60% chance of winning the next election, this expresses the forecasters’ degree of certainty on the basis of their knowledge, not some relative frequency. This interpretation seems well-suited for historical reconstruction as well. A statement such as “With 60% probability, Italic and Celtic form a common sub-group of Indo-European.” is coherent unter the Bayesian, but not under the frequentist interpretation.“ (P. 26)

Kita, E., 2011 Evolutionary algorithms. Rijeka: InTech.

“Evolutionary algorithms (EAs) are the population-based metaheuristic optimization algorithms. Candidate solutions to the optimization problem are defined as individuals in a population, and evolution of the population leads to finding better solutions. The fitness of individuals to the environment is estimated and some mechanisms inspired by biological evolution are applied to evolution of the population. Genetic algorithm (GA), Evolution strategy (ES), Genetic programming (GP), and Evolutionary programming (EP) are very popular Evolutionary algorithms.” (P. ix)

Hall, D. and Klein, D., 2010, July. Finding cognate groups using phylogenies. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (pp. 1030-1039). Association for Computational Linguistics.

“In this paper, we present a new generative model for the automatic induction of cognate groups given only (1) a known family tree of languages and (2) word lists from those languages. A prior on word survival generates a number of cognate groups and decides which groups are attested in each modern language. An evolutionary model captures how each word is generated from its parent word. Finally, an alignment model maps the flat word lists to cognate groups. Inference requires a combination of message-passing in the evolutionary model and iterative bipartite graph matching in the alignment model.” (P. 1031)

[officialsmbe]

Practical Speedup of Bayesian Inference of Species Phylogenies by Restricting the Space of Gene Trees

MBE latest: http://dlvr.it/RQQlJK