[Bioinformatics] please drop me from your list, thanks.

Bioinformatics IDP-Seminar Series bioinformatics at lists.ucla.edu
Wed Apr 22 14:29:35 PDT 2009


>
> MONDAY, April 27, 2009
> 4:00pm
> CNSI Auditorium
> Ian Holmes, Ph.D.
> Department of Bioengineering, UC Berkeley
>
> "Evolutionary Grammars of Genes and Genomes: Dynamic ProgrammingAlgorithms
> for Ancestral Sequence Reconstruction"
> Abstract:
> Several statistical (and score-empirical) models can be used to
> reconstruct molecular evolutionary history, predicting past and future
> gene (protein-coding, RNA, etc.) and genome sequences. This is done by
> aligning sequence data from various different time-points, including (any
> or all of) the present day/epoch; serially-space timepoints (for
> fast-evolving samples, e.g. viruses); and/or "paleogenetic" sequence data
> obtained from partially-degraded fossils. Statistically, one can think of
> this all as a directed-tree graphical model. The variables at the graph
> nodes are sequences. The graph edges representing evolutionary time
> intervals (or, for imperfect sequence recovery, degradative intervals).
> For inference under this model we can adopt standard Bayesian techniques.
> MCMC and various empirically-motivated ML/EM steps can be designed around
> finite-state machines that mutate strings. Although the sequences are
> infinite, certain well-formed subproblems can be solved exactly. We have
> developed several UNIX simulation and inference tools that allow us to ask
> simulation-answerable questions (e.g. "How much of the past is knowable?")
> as well as empirically-answerable questions (e.g. "predict probable
> ancestral sequences for all protein domains in PFAM, or RNA domains in
> RFAM"). Curiously, language evolution follows patterns that are
> mathematically identical to genes (at a certain level of abstraction).
> http://bioeng.berkeley.edu/cv/iholmes.php
>
> Host: Matteo Pellegrini
> *Refreshments will be served after the seminar at 5:00 pm*
>
>
>
>
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>
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