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title title. Robustness, clustering & evolutionary conservation. Stefan Wuchty Center of Network Research Department of Physics University of Notre Dame. New York Times. Complex systems. Made of many non-identical elements connected by diverse interactions. NETWORK. Bio-Map. GENOME.

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titletitle

Robustness, clustering &evolutionary conservation

Stefan Wuchty

Center of Network Research

Department of Physics

University of Notre Dame


New York Times

Complex systems

Made of many non-identical elements connected by diverse interactions.

NETWORK


Bio-Map

GENOME

protein-gene interactions

PROTEOME

protein-proteininteractions

METABOLISM

Bio-chemical reactions

Citrate Cycle


Bio-Map

PROTEOME

protein-proteininteractions


Prot Interaction map

Yeast protein network

Nodes: proteins

Links: physical interactions (binding)

P. Uetz, et al. Nature, 2000; Ito et al., PNAS, 2001; …


Prot P(k)

Topology of the protein network

H. Jeong, S.P. Mason, A.-L. Barabasi & Z.N. Oltvai, Nature, 2001


Robustness

1

node failure

S

fc

0

1

Fraction of removed nodes, f

Robustness

Complex systems maintain their basic functions even under errors and failures (cell  mutations; Internet  router breakdowns)


Robust-SF

Failures

Topological error tolerance

  3 : fc=1

(R. Cohen et. al., PRL, 2000)

fc

Attacks

Robustness of scale-free networks

1

R. Albert et.al.

Nature, 2000

S

0

f

1


Prot- robustness

Yeast protein network

- lethality and topological position -

Highly connected proteins are more essential (lethal)...

H. Jeong et al., Nature, 2001


Metabolic networks

Protein networks

Modules in biological systems

E. Ravasz et al.,Science, 2002


Can we identify the modules?

J(i,j): # of nodes both i and j link to; +1 if there is a direct (i,j) link


Metabolism: E. Ravasz et al.,Science, 2002

Protein interactions: Rives and Galitski, PNAS, 2003

Spirin and Mirny, PNAS, 2003


Open questions

Does the application of standart clustering

algorithms reflect real modules well?

Since e.g. one protein can be part of more

than one protein complex overlapping

clustering algorithms should give better

results.


Motifs

Small subnetworks that appear in real world networks significantly more often than in random graphs.

(Milo et al., Science, 2002; Conant and Wagner, Nature Gen., 2003, Shen-Orr et al., Nature Gen., 2002, Milo et al, Science, 2004)


From theparticularto theuniversal

A.-L- Barabasi & Z. Oltvai, Science, 2002


Topology and Evolution


Topology and Evolution

S. Wuchty, Z. Oltvai & A.-L. Barabasi, Nature Genetics, 2003


Topology and evolution

- General distribution of orthologs:

E = N(o)/N(p)

- degree-dependent distribution

of orthologs

ek = Nk(o)/Nk

Orthologous Excess Retention:

ERk = ek/E

S. Wuchty, Genome Res., 2004


Clustering in protein interaction networks

high clustering = high quality of interaction

Goldberg and Roth, PNAS, 2003


Does that also hold for evolutionary conservation?


Protein-protein interaction data

are highly flawed:

90% false positives, 50% false negatives

Von Mering et al., Nature, 2002

How stable are these results?


Something else?

Eisen et al., PNAS, 1998


Open question

?

?

Wuchty et al., submitted, 2004


Plasmodium falciparum

  • Eukaryotic organism

  • Malaria parasite

  • Genome size 23 MB, 14 chromosomes

  • 5300 genes (estimated, Hall et al., Nature 2002, Gardner et al., Nature, 2002)

  • No protein interaction data available

  • Co-expression data available (Bozdech et al., PloS, 2003, LeRoch et al., Science, 2003)

  • 868 orthologs with Yeast (InParanoid, Remm et al. J. Mol. Biol., 2001)


Plasmodium falciparum


Plasmodium falciparum


  • Iteratively pruning edges starting with the least weighted link

  • Quality of clusters is assessed by their modularity

until a maximum is reached.

Inferred protein interaction networkin P. falciparum

  • 667 nodes, 3,564 weighted interactions

  • Clustering


All edges shown with Cvw > 1.

Colorcode red: Cvw > 4, yellow: Cvw > 3,

green: Cvw > 2, blue: Cvw > 1


Co-expression patterns

Bozdech et al. PLoS, 2003

What does that mean?

Validation of results?


ribososome

RNA processing

translation

DNA processing

exo/protesome

replication

Wuchty, Barabasi, Ferdig and Adams, in preperation


What‘s next?

  • Uncovering evolutionary cores of interactions in other organisms.

  • Application of a Maximum Set Cover Algorithm to predict protein interactions (Huang, Kaanan, Wuchty, Izaguirre and Cheng, submitted) to unfold the interactome using the evolutionary cores and experimentally derived interactions.


T H X !

http:[email protected]


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