protein networks as a scaffold for structuring other data

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Protein networks as a scaffold for structuring other data Lars Juhl Jensen EMBL Heidelberg

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Protein networks as a scaffold for structuring other data

Lars Juhl Jensen

EMBL Heidelberg

cell cycle regulation

Chapter 1

interaction networks

what is an interaction?

functional interactions

physical interactions

yeast two-hybrid

complex pull-down

high-throughput

S. cerevisiae

Uetz et al.

Ito et al.

Gavin et al.

Ho et al.

Gavin et al.

Krogan et al.

C. elegans

Li et al.

D. melanogaster

Giot et al.

H. sapiens

Stelzl et al.

Rual et al.

yeehaa!

network topology

degree distribution

scale-free

hubs

essentiality

network robustness

targeted attacks

artefacts

self-activating baits

highly expressed proteins

Han et al.

can we trust this data?

the human interactome

(incomplete)

yeast two-hybrid

1936

13

4

4

1385

65

18465

Stelzl et al. Rual et al.

Small-scale studies

32

0

3

4

18

4

23

Stelzl et al. Rual et al.

Small-scale studies

62 8 39

Small-scale studies

Stelzl et al. Rual et al.

852

17

473

432

69

260

3.5% and 21% sensitivity

the yeast interactome

five years ago

yeast two-hybrid

1150

117

117

72

4053

118

4469

Uetz et al. Ito et al.

Small-scale studies

162

53

34

72

180

29

338

Uetz et al. Ito et al.

Small-scale studies

511 189 616

Small-scale studies

Uetz et al. Ito et al.

439

178

759

897

190

1347

19% and 12% sensitivity

three years ago

complex pull-down

14186

784

1178

287

19492

230

3475

Gavin et al. Ho et al.

Small-scale studies

2341

125

656

287

2725

42

149

Gavin et al. Ho et al.

Small-scale studies

4431 1465 5041

Small-scale studies

Gavin et al. Ho et al.

14913

1071

632

8047

517

746

63% and 41% sensitivity

what about accuracy?

30–50% specificity

what can we do about it?

topology-based scoring

complex pull-down

log[(N12·N)/((N1+1)·(N2+1))]

yeast two-hybrid

-log((N1+1)·(N2+1))

calibrate against KEGG

subcellular localization

filtering

high-throughput

high-confidence

Chapter 2

expression data

S. cerevisiae

synchronized cell culture

microarray time series

periodically expressed genes

S. cerevisiae

Cho et al.

Spellman et al.

yeehaa!

Zhao et al.

Langmead et al.

Johansson et al.

Wichert et al.

Luan and Li

Lu et al.

Ahdesmäki et al.

Willbrand et al.

Chen et al.

Qiu et al.

Ahnert et al.

Andersson et al.

no benchmarking

reanalysis

benchmarking

no progress

no benchmarking

Chapter 3

1+2 = 3

expression data

protein interactions

temporal network

benchmarking

very low error rate

discovery tool

30+ uncharacterized proteins

detailed function prediction

novel module

global statements

dynamic and static

CDK–cyclin complexes

consistent timing

pre-replication complex

just-in-time assembly

how can we test this?

evolutionary conservation

Chapter 4

more expression data

S. cerevisiae

microarray time series

periodically expressed genes

S. pombe

Rustici et al.

(good job)

Peng et al.

Oliva et al.

no benchmarking

no integration

reanalysis

benchmarking

no progress

no benchmarking

no integration

H. sapiens

Whitfield et al.

reanalysis

benchmarking

A. thaliana

Menges et al.

reanalysis

benchmarking

list of genes

peak times

Chapter 5

cross-species comparison

orthology assignment

peak times

not comparable

time warping

not conserved

individual genes

just-in-time assembly

protein complexes

DNA polymerases

pre-replication complex

chromatid cohesion

reproduces what is known

known differences

timing has changed

identity has changed

self-consistent

make sense

protein complexes

individual genes

broader perspective

protein networks

context

understanding

Acknowledgments

Ulrik de LichtenbergThomas Skøt JensenChristian von Mering

Søren BrunakPeer Bork