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Lars Juhl Jensen
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IPAM Proteomics Reunion Conference, UCLA, Lake Arrowhead, California, December 11-16, 2005
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Integration of diverse large-scale datasets
1.
Integration of diverse
large-scale datasets
2.
Lars Juhl Jensen
3.
4.
5.
6.
promoter analysis
7.
Jensen et al.,
Bioinformatics, 2000
8.
DNA structure
9.
genome visualization
10.
Pedersen et al.,
Journal of Molecular Biology, 2000
11.
microarray normalization
12.
Workman et al.,
Genome Biology, 2002
13.
protein function prediction
14.
15.
16.
17.
18.
STRING
19.
20.
integrate diverse evidence
21.
functional interactions
22.
Bork et al.,
Current Opinion in Structural Biology, 2005
23.
179 proteomes
24.
evolution
25.
26.
27.
statistics
28.
(the original sin)
29.
prokaryotes
30.
genomic context methods
31.
gene fusion
32.
33.
gene neighborhood
34.
35.
phylogenetic profiles
36.
37.
38.
39.
40.
Cell Cellulosomes Cellulose
41.
eukaryotes
42.
integrate diverse datasets
43.
Jensen et al.,
Drug Discovery Today: Targets, 2004
44.
curated knowledge
45.
MIPS Munich Information
center for Protein Sequences
46.
KEGG Kyoto Encyclopedia
of Genes and Genomes
47.
STKE Signal Transduction
Knowledge Environment
48.
Reactome
49.
literature mining
50.
M EDLINE
51.
SGD Saccharomyces Genome
Database
52.
The Interactive Fly
53.
OMIM Online Mendelian
Inheritance in Man
54.
co-mentioning
55.
NLP Natural Language
Processing
56.
57.
58.
primary experimental data
59.
microarray expression data
60.
GEO Gene Expression
Omnibus
61.
physical protein interactions
62.
BIND Biomolecular Interaction
Network Database
63.
MINT Molecular Interactions
Database
64.
GRID General Repository
for Interaction Datasets
65.
DIP Database of
Interacting Proteins
66.
HPRD Human Protein
Reference Database
67.
problems
68.
many sources
69.
(different gene identifiers)
70.
many types of
evidence
71.
questionable quality
72.
not directly comparable
73.
spread over many
species
74.
huge synonyms lists
75.
calculate raw quality
scores
76.
calibrate vs. gold
standard
77.
KEGG Kyoto Encyclopedia
of Genes and Genomes
78.
von Mering et
al., Nucleic Acids Research, 2005
79.
transfer based on
orthology
80.
combine all evidence
81.
Bork et al.,
Current Opinion in Structural Biology, 2005
82.
cell cycle
83.
qualitative modeling
84.
85.
Chen et al.,
Molecular Biology of the Cell, 2004
86.
Chen et al.,
Molecular Biology of the Cell, 2004
87.
synchronized cell culture
88.
89.
microarray time series
90.
91.
periodically expressed genes
92.
93.
S. cerevisiae
94.
Cho et al.
95.
Spellman et al.
96.
numerous analysis methods
97.
Cho et al.
98.
Spellman et al.
99.
Zhao et al.
100.
Johansson et al.
101.
Luan and Li
102.
Lu et al.
103.
Ahdesm äki et
al.
104.
Willbrand et al.
105.
no benchmarking
106.
de Lichtenberg et
al., Bioinformatics, 2005
107.
reproducibility
108.
de Lichtenberg et
al., Bioinformatics, 2005
109.
regulation vs. periodicity
110.
de Lichtenberg et
al., Bioinformatics, 2005
111.
list of 600
periodic genes
112.
S. pombe
113.
several expression studies
114.
reproducibility
115.
Marguerat et al.,
Yeast, 2006
116.
name inconsistencies
117.
Marguerat et al.,
Yeast, 2006
118.
different analysis methods
119.
no benchmarking
120.
Marguerat et al.,
Yeast, 2006
121.
Marguerat et al.,
Yeast, 2006
122.
too many genes
suggested
123.
Marguerat et al.,
Yeast, 2006
124.
Marguerat et al.,
Yeast, 2006
125.
averaging better than
voting
126.
Marguerat et al.,
Yeast, 2006
127.
S. cerevisiae
128.
list of 600
periodic genes
129.
protein interaction data
130.
131.
von Mering et
al., Nucleic Acids Research, 2005
132.
de Lichtenberg et
al., Science, 2005
133.
dynamic proteins
134.
static proteins
135.
de Lichtenberg et
al., Science, 2005
136.
reproduces what is
known
137.
de Lichtenberg et
al., Science, 2005
138.
many detailed predictions
139.
de Lichtenberg et
al., Science, 2005
140.
global trends
141.
dynamic proteins
142.
de Lichtenberg et
al., Science, 2005
143.
static proteins
144.
de Lichtenberg et
al., Science, 2005
145.
just-in-time assembly
146.
de Lichtenberg et
al., Science, 2005
147.
de Lichtenberg et
al., Science, 2005
148.
coordinated regulation
149.
periodically expressed genes
150.
Cdc28p substrates
151.
PEST degradation signals
152.
the human interactome
153.
yeast two-hybrid
154.
1936 13 4
4 1385 65 18465 Stelzl et al. Rual et al. Small-scale studies
155.
32 0 3
4 18 4 23 Stelzl et al. Rual et al. Small-scale studies
156.
62 8 39
Small-scale studies Stelzl et al. Rual et al. 852 17 473 432 69 260
157.
3.5% and 21%
sensitivity
158.
in a couple
of years
159.
the human interactome
160.
100% = 1/5?
161.
the yeast interactome
162.
five years ago
163.
yeast two-hybrid
164.
1150 117 117
72 4053 118 4469 Uetz et al. Ito et al. Small-scale studies
165.
162 53 34
72 180 29 338 Uetz et al. Ito et al. Small-scale studies
166.
511 189 616
Small-scale studies Uetz et al. Ito et al. 439 178 759 897 190 1347
167.
19% and 12%
sensitivity
168.
the challenge
169.
how to get
from here …
170.
1936 13 4
4 1385 65 18465 Stelzl et al. Rual et al. Small-scale studies
171.
… to
there …
172.
de Lichtenberg et
al., Science, 2005
173.
174.
Thank you!
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