The first book to make an appearance that explicitly deals
with phylogenetic networks was:
D. H. Huson, R. Rupp and C. Scornavacca (2011) Phylogenetic Networks: Concepts, Algorithms and Applications. Cambridge University Press. [Dated 2010 but
published January 17 2011] Available in hardback ISBN:978-0-521-75596-2 and as
an eBook ISBN:978-0-511-92242-8.
In addition to the three reviews that appear as part of the
publisher's blurb, a number of independent book reviews have appeared since its
publication:
Tiratha Raj Singh (2011) Current Science 100: 1570-1571.
Paul Cull (2011) Computing Reviews Review#139416.
Steven Kelk (2012) Systematic Biology 61: 174-175.
Jim Whitfield (2012) Systematic Biology 61: 176-177.
These are all worth reading, but I wish to comment here on
one particular review, the one by Steven Kelk. This review makes two points
about current network methods that seem to me not to have been sufficiently
emphasized in other publications. The review itself is thus an important
contribution to the literature on phylogenetic networks.
(1) Rooted networks based on a "hybridization"
model can be derived by combining clusters, triplets or trees. [Note: combining
characters usually leads to a "recombination" model.] However, only
by combining trees do the reticulation vertices in the resulting network
explicitly model reticulate evolutionary events (e.g. hybridization or
horizontal gene transfer); for clusters and triplets the reticulation vertices
can be abstract. This has important practical consequences for biologists, who
routinely interpret rooted networks as though all of the vertices (nodes)
represent inferred ancestors undergoing "descent with modification"
(as Charles Darwin called it). There has been insufficient attention paid to
this point in the literature on cluster and triplet methods.
Note that this point does not deny any intrinsic
mathematical interest in clusters and triplets (which Steven, himself,
emphasizes in his own research work). Nor does it deny any possible use of them
in practical network methods; indeed, I have seen them work quite well in
practice. The point is simply that the tree model explicitly provides something
that biologists find valuable, and which (I would argue) has been principally
responsible for the widespread use of that model in phylogenetics. One can even
argue that phylogenetic analysis is the inference of vertices in a
tree/network. (If you look at Darwin’s only published tree you will note that
it is the vertices of his tree that are missing, indicating his explicit doubt
about the feasibility of inferring them.)
(2) Great attention has been paid in the literature to
certain topologically restricted sub-families of rooted networks (such as galled
networks, level-k networks, etc). These theoretical classes have been chosen
because of concerns about computational tractability, rather than anything to
do with the priorities of biological modeling. Unfortunately, little attention
has been paid to how likely these networks are from the biological viewpoint.
Perhaps the only other unequivocal publication on this topic is that of (M. Arenas, M. Patricio, D. Posada, G. Valiente. 2010. Characterization of phylogenetic
networks with NetTest. BMC Bioinformatics 11: 268) More work needs to be
done to address this uncertain applicability.
Steven's review appeared in Systematic Biology,
which actually has a long tradition of original book reviews that are worth
citing in formal research publications. For example, one of the more highly
cited papers in the journal is the book review in which Don Colless published
his tree-imbalance formula (D.H. Colless. [Review of] Phylogenetics: the Theory
and Practice of Phylogenetic Systematics. Systematic Zoology 1982, 31:100-104), which receives continual citation
because the formula is still commonly used today. Not everyone publishes
original research in their book reviews!
Declaration of potential competing interest: I am currently
the Book Review Editor for Systematic Biology, and so I am the one
who commissioned Steven's review. However, I take no credit for the contents of
the review! The numerous reviewers I have dealt with over the years have
produced reviews that varied from excellent through mediocre to ones that
needed extensive revision, and on to two that I wrote myself when the original
reviewer failed to deliver.
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