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Computing the Tree of Life

The University of Texas at Austin

Department of Computer Sciences

Tandy Warnow

PhylogenyFrom the Tree of the Life Website,

University of Arizona

Orangutan Gorilla Chimpanzee Human

DNA Sequence Evolution

AAGACTT

TGGACTTAAGGCCT

-3 mil yrs

-2 mil yrs

-1 mil yrs

today

AGGGCAT TAGCCCT AGCACTT

AAGGCCT TGGACTT

TAGCCCA TAGACTT AGCGCTTAGCACAAAGGGCAT

AGGGCAT TAGCCCT AGCACTT

AAGACTT

TGGACTTAAGGCCT

AGGGCAT TAGCCCT AGCACTT

AAGGCCT TGGACTT

TAGCCCA TAGACTT AGCGCTTAGCACAAAGGGCAT

AGGGCAT TAGCCCT AGCACTT

Molecular Phylogenetics

TAGCCCA TAGACTT TGCACAA TGCGCTTAGGGCAT

U V W X Y

U

V W

X

Y

(Tree is unrooted)

Evolutionary trees and the pharmaceutical industry

• Big genome sequencing projects just produce data -- so what? Evolutionary history relates all organisms and genes, and evolutionary trees are used to make important biological discoveries.

• The pharmaceutical industry uses phylogenies for many applications, such as the development of influenza vaccine!

• Inaccuracies in the phylogenies lead to inaccurate predictions (e.g., vaccines that don’t work, drugs that don’t have the required properties). Current software isn’t accurate enough, or fast enough!

• This means $$$!

We are world leaders in research in Computational Phylogenetics

• “DCM-boosting” for phylogeny reconstruction - improves accuracy and speeds up heuristics for NP-hard problems (Warnow, UT-Austin)

• GRAPPA -- software for whole genome phylogeny (Moret, UNM)

• Visualization of large trees, and sets of trees (Amenta, UC Davis)

• Phylogenetic databases (Miranker)

DCM-boosting phylogenetic reconstruction methods[Nakhleh et al. ISMB 2001]

• DCM-boosting makes fast methods more accurate

• DCM-boosting speeds-up heuristics for hard optimization problems

NJ

DCM-NJ

0 400 800 16001200No. Taxa

0

0.2

0.4

0.6

0.8

Err

or R

ate

Whole-Genome Phylogenetics

A

B

C

D

E

F

X

Y

ZW

A

B

C

D

E

F

Benchmark gene order dataset: Campanulaceae

• 12 genomes + 1 outgroup (Tobacco), 105 gene segments• NP-hard optimization problems: breakpoint and inversion

phylogenies

1997: BPAnalysis (Blanchette and Sankoff): 200 years (est.)

Benchmark gene order dataset: Campanulaceae

• 12 genomes + 1 outgroup (Tobacco), 105 gene segments• NP-hard optimization problems: breakpoint and inversion

phylogenies

1997: BPAnalysis (Blanchette and Sankoff): 200 years (est.)2000: Using GRAPPA v1.1 on the 512-processor Los Lobos

Supercluster machine: 2 minutes (200,000-fold speedup per processor)

Benchmark gene order dataset: Campanulaceae

• 12 genomes + 1 outgroup (Tobacco), 105 gene segments• NP-hard optimization problems: breakpoint and inversion

phylogenies

1997: BPAnalysis (Blanchette and Sankoff): 200 years (est.)2000: Using GRAPPA v1.1 on the 512-processor Los Lobos

Supercluster machine: 2 minutes (200,000-fold speedup per processor)

2003: Using latest version of GRAPPA: 2 minutes on a single processor (1-billion-fold speedup per processor)

GRAPPA (Genome Rearrangement Analysis under Parsimony and other

Phylogenetic Algorithms)http://www.cs.unm.edu/~moret/GRAPPA/

• Heuristics for NP-hard optimization problems

• Fast polynomial time distance-based methods

• Contributors: U. New Mexico,U. Texas at Austin, Universitá di Bologna, Italy

• Fastest and most accurate software for whole genome phylogeny worldwide

Opportunities

• New phylogenetic reconstruction software can improve pharmaceutical R&D (making more accurate solutions achievable in hours or days, rather than months or years)

• Software for researchers is available as free (open source), but users need the latest tools now, with proper interfaces -- business opportunity.

Participants and Funding

• University of Texas Computer Scientists: Warnow, Dhillon, Hunt, and Miranker

• University of Texas biologists: Jansen, Linder, and Hillis

• Other institutions: UNM, UC Davis, Central Washington, CUNY, JGI

• Funding: Three NSF ITR grants, NSF Biocomplexity, David and Lucile Packard Foundation

Phylolab, U. TexasPlease visit us athttp://www.cs.utexas.edu/users/phylo/

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