[Colloquium] [CDAC] TODAY: Tandy Warnow (UIUC), Noon, JCL 390

[Rob Mitchum]

*Tandy Warnow*
*Founder Professor of Computer Science*
*University of Chicago*

*Theoretical and Empirical Advances in Large-Scale Species Tree Estimation
         *
*Friday, May 24, 2019 @ 12:00pm*
*John Crerar Library <https://goo.gl/maps/5h7saQhVerqW8gYA9>, Room 390*
*Lunch Provided*

The estimation of the "Tree of Life" -- a phylogeny encompassing all life
on earth--is one of the big Scientific Grand Challenges.  Maximum
likelihood (ML) is a standard approach for phylogeny estimation, but
estimating ML trees for large heterogeneous datasets is challenging for two
reasons: (1)  ML tree estimation is NP-hard (and the best current
heuristics can use hundreds of CPU years on relatively small datasets, just
to find local optima), and (2) the statistical models used in ML tree
estimation methods are much too simple, failing to acknowledge
heterogeneity across genomes or across the Tree of Life.  These two "big
data" issues -- dataset size and heterogeneity -- impact the accuracy of
phylogenetic methods and have consequences for downstream analyses.

In this talk, I will describe a new "divide-and-conquer" approach to
phylogeny estimation that addresses both types of heterogeneity. Our
protocol operates as follows: (1) we divide the set of species into
disjoint subsets, (2) we construct trees on the subsets (using appropriate
statistical methods), and (3) we combine the trees together using auxiliary
information, such as a matrix of pairwise distances. I will present three
such strategies (all published in the last year) that operate in this
fashion, and that improve the theoretical and empirical performance of
phylogeny estimation methods. One of the main applications of this work is
species tree estimation from multi-locus data sets when gene trees can
differ from the species tree due to incomplete lineage sorting.  This talk
is largely based on joint work with my PhD student, Erin Molloy (Illinois).

*Bio:*

Tandy Warnow is the Founder Professor of Computer Science at the University
of Illinois at Urbana-Champaign, where she is also an affiliate in
Mathematics, Statistics, Bioengineering, Electrical and Computer
Engineering, Animal Biology, Entomology, and Plant Biology. Tandy received
her PhD in Mathematics at UC Berkeley under the direction of Gene Lawler,
and did postdoctoral training with Simon Tavaré and Michael Waterman at
USC. Her research combines computer science, statistics, and discrete
mathematics, focusing on developing improved models and algorithms for
reconstructing complex and large-scale evolutionary histories in biology
and historical linguistics. She has published more than 160 papers and one
textbook, graduated 11 PhD students, and has 5 current PhD students. She
has been a visiting faculty member at many universities, including
Princeton University, the University of Maryland, Yale University, Ecole
Polytechnique Fédérale de Lausanne (EPFL), and Harvard University. Her
awards include the NSF Young Investigator Award (1994), the David and
Lucile Packard Foundation Award (1996), a Radcliffe Institute Fellowship
(2006), and the John Simon Guggenheim Foundation Fellowship (2011). She was
elected a Fellow of the Association for Computing Machinery (ACM) in 2015
and of the International Society for Computational Biology (ISCB) in 2017.
Her national service includes being the lead NSF program officer for
BigData (2012-2013), chairing the BioData Management and Analysis (BDMA)
study section at NIH (2010-2012). Tandy was also a member of the Big Data
Senior Steering Group of NITRD subcommittee of the National Technology
Council (coordinating federal agencies), 2012-2013.



-- 
*Rob Mitchum*

*Associate Director of Communications for Data Science and Computing*
*University of Chicago*
*rmitchum at uchicago.edu <rmitchum at ci.uchicago.edu>*
*773-484-9890*
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