... A tree is a connected, acyclic 2D graph
Tree length = sum of all branch lengths
Phylogenetic trees are binary trees
... Organize a collection of modern-day sequences according to their evolutionary history
Distance-based methods operate on a table of pairwise distances between sequences
o UPGMA: ~agglomerative clustering; naïve method for tree-building; assumes a molecular clock
(all branches changing at the same ...
... • Breakthrough: Optimal logarithmic sequence length tree reconstruction
(Daskalakis, Mossel, Roch 05). Simpliﬁed version (Mihaescu et al. 06).
Preliminary Implementation [Adkins et al.].
Introduction to Phylogenetics - Lectures For UG-5
... Making trees using character-based
The main idea of character based methods is to search for a tree
that requires the smallest number of evolutionary changes to
explain the differences among the OTUs under study.
... involves two different data types (for instance, GWAS and expression data, as in eQTL
analyses). The availability of more than 2 omics data types derived from the same set of
individuals is rare. And when these exist, several technical and statistical hurdles need
to be taken to ensure optimal power ...
Creating Phylogenetic Trees with MEGA
... – At each site, the likelihood is determined by evaluating the
probability that a certain evolutionary model (eg. BLOSSUM or
PAM matrices) has generated the observed data.
– The likelihood’s for each site are then multiplied to provide
likelihood for each tree
– Choose the tree with maximum like ...
... Pairwise distance and neighbor
joining are distance methods.
• There are two main categories of phylogeny
methods, distance methods and character
methods. In distance methods, the first step
is to calculate a matrix of all pairwise
differences between a set of sequences.
Next, the tree is construct ...
... – UT CS: Tandy Warnow, Luay Nakhleh
– UT BIO: Randy Linder
– UNM CS: Bernard Moret
... Each edge represents an entry in our cognate-percentage matrix. They are color-coded by
A Large Margin Method for Semi
... labeled data. This imposes a great challenge in that the class probability given input can not be
well estimated through labeled data alone. In this talk, I will present a large margin semisupervised method based on an efficient margin loss for unlabeled data. This loss seeks
extracting the maximum ...
BlueJam Evolutionary Music Composition
... Genetic Programming (GP) and Evolutionary Algorithms (EA) have
produced human-competitive results when applied to problems of
all kinds. Their approach to problem solving can be described as a
search through the space of possible solutions.
In 1992, Koza brought Tree-based GP to prominence, and it h ...
A method for paralogy trees reconstruction
... Genes belonging to the same organism are called paralogs when they show a significant similarity
in the sequences, even if they have a different biological function. It is an emergent biological
paradigm that the families of paralogs derive from a mechanism of gene duplication with
modification, rep ...
... Bootstrapping phylogenies
Characters are resampled with replacement to
create many bootstrap replicate data sets
Each bootstrap replicate data set is analysed (e.g.
with parsimony, distance, ML etc.)
Agreement among the resulting trees is
summarized with a majority-rule consensus tree
characters work the
same (idea is there
may be more
more of them)
... Two brief categories of investigation
Each one has two parts
Using HIV Data Sets for Inquiry
... Split decomposition is one method for testing a tree.
Under this procedure, we choose exactly four taxa (A, B, C, D)
and examine the topologies of all possible unrooted trees. How
many such trees are there?
Phylogeny of the Primates
... As promised, you are going to get your chance to create a phylogenetic tree from some
molecular clock data. We are going to give you some mutation differences in DNA.
This is just like the bird phylogeny we did. Below is a table of REAL data. This date
represents difference in DNA. It is obtained by ...
Marked Patterns of Lexical Borrowing in Southeast Asia Uri Tadmor
... Some features of Southeast Asian languages are shared among many languages of the region,
regardless of genetic affiliation. When taken together, such areal features permit us to
consider Southeast Asia as a linguistic area. The more universally marked these features, the
stronger evidence they cons ...
Quantitative comparative linguistics
Statistical methods have been used in comparative linguistics since at least the 1950s (see Swadesh list). Since about the year 2000, there has been a renewed interest in the topic, based on the application of methods of computational phylogenetics and cladistics to define an optimal tree (or network) to represent a hypothesis about the evolutionary ancestry and perhaps its language contacts. The probability of relatedness of languages can be quantified and sometimes the proto-languages can be approximately dated.The topic came the attention of the popular press in 2003 after the publication of a short study on Indo-European in Nature (Gray and Atkinson 2003). A volume of articles on Phylogenetic Methods and the Prehistory of Languages was published in 2006 as the result of a conference held in Cambridge in 2004.A goal of comparative historical linguistics is to identify instances of genetic relatedness amongst languages. The steps in quantitative analysis are (i) to devise a procedure based on theoretical grounds, on a particular model or on past experience, etc. (ii) to verify the procedure by applying it to some data where there exists a large body of linguistic opinion for comparison (this may lead to a revision of the procedure of stage (i) or at the extreme of its total abandonment) (iii) to apply the procedure to data where linguistic opinions have not yet been produced, have not yet been firmly established or perhaps are even in conflict.Applying phylogenetic methods to languages is a multi-stage process (a) the encoding stage - getting from real languages to some expression of the relationships between them in the form of numerical or state data, so that those data can then be used as input to phylogenetic methods (b) the representation stage - applying phylogenetic methods to extract from those numerical and/or state data a signal that is converted into some useful form of representation, usually two dimensional graphical ones such as trees or networks, which synthesise and ""collapse"" what are often highly complex multi dimensional relationships in the signal (c) the interpretation stage - assessing those tree and network representations to extract from them what they actually mean for real languages and their relationships through time.