Cartography of metabolism and its uses in assessing data reliability and understanding cellular network functionality Adam Pah Thesis June 1, 2013 1
Adam Pah, Dissertation presentation at Northwestern University on the cartography of metabolic networks
Jun 24, 2015
Dissertation presentation on "Cartography of metabolism and its uses in assessing data reliability and understanding cellular network functionality".
Presented at Northwestern University on June 4, 2013 in order to attain the degree of Doctor of Philosophy in Biological Sciences.
Goes along with the publication "Use of a global metabolic network to curate organismal metabolic networks" found at:
http://www.nature.com/srep/2013/130422/srep01695/full/srep01695.html
and the MetExplore application found at:
metexplore.npcompleteheart.com
Presented at Northwestern University on June 4, 2013 in order to attain the degree of Doctor of Philosophy in Biological Sciences.
Goes along with the publication "Use of a global metabolic network to curate organismal metabolic networks" found at:
http://www.nature.com/srep/2013/130422/srep01695/full/srep01695.html
and the MetExplore application found at:
metexplore.npcompleteheart.com
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Transcript
Cartography of metabolism and its uses in assessing data reliability and understanding
cellular network functionality
Adam Pah Thesis
June 1, 2013
���1
Where do we stand and how can we do better?
���2
Where do we stand and how can we do better?
We are generating biological data faster than ever
���2
Where do we stand and how can we do better?
We are generating biological data faster than ever
But generating is only one part, we still have to convert that to actual usable knowledge
���2
Knowledge
Where do we stand and how can we do better?
We are generating biological data faster than ever
But generating is only one part, we still have to convert that to actual usable knowledge
���2
KnowledgeData
Where do we stand and how can we do better?
We are generating biological data faster than ever
But generating is only one part, we still have to convert that to actual usable knowledge
���2
KnowledgeData
Know
ledge
Why metabolism?
���3
Why metabolism?
���3
Why metabolism?
���3
• My goal is to create a generalizable framework for understanding cellular networks
!
• Define the global framework
• Curating organismal networks
• Finding intermediate structures
• Identify community structure
• Visualizing metabolism at depth
Talk Outline
���4
!
• Define the global framework
• Curating organismal networks
• Finding intermediate structures
• Identify community structure
• Visualizing metabolism at depth
Talk Outline
���4
!
• Define the global framework
How do we construct a metabolic network
Metabolic networks are constructed from the Kyoto Encyclopedia of Genes and Genomes database for each organism where:
How do we construct a metabolic network
Metabolic networks are constructed from the Kyoto Encyclopedia of Genes and Genomes database for each organism where:
• Metabolites are connected if they are a part of the main reaction pair
How do we construct a metabolic network
Metabolic networks are constructed from the Kyoto Encyclopedia of Genes and Genomes database for each organism where:
• Metabolites are connected if they are a part of the main reaction pair
• Substrates are connected to Products only.
How do we construct a metabolic network
Metabolic networks are constructed from the Kyoto Encyclopedia of Genes and Genomes database for each organism where:
• Metabolites are connected if they are a part of the main reaction pair
• Substrates are connected to Products only.
How do we construct a metabolic network
UDP-Glucose + H2O + 2 NAD+ UDP-Glucuronate + 2 NADH + 2 H+
Metabolic networks are constructed from the Kyoto Encyclopedia of Genes and Genomes database for each organism where:
• Metabolites are connected if they are a part of the main reaction pair
• Substrates are connected to Products only.
How do we construct a metabolic network
UDP-Glucose + H2O + 2 NAD+ UDP-Glucuronate + 2 NADH + 2 H+UDP-Glucose + H2O + 2 NAD+ UDP-Glucuronate + 2 NADH + 2 H+
Metabolic networks are constructed from the Kyoto Encyclopedia of Genes and Genomes database for each organism where:
• Metabolites are connected if they are a part of the main reaction pair
• Substrates are connected to Products only.
How do we construct a metabolic network
UDP-Glucose + H2O + 2 NAD+ UDP-Glucuronate + 2 NADH + 2 H+UDP-Glucose + H2O + 2 NAD+ UDP-Glucuronate + 2 NADH + 2 H+
UDP-Glucose UDP-Glucuronate
2 NAD+ 2 NADH
Looking at one organism
���6
Methanococcus maripaludis
Looking at one organism
���6
Methanococcus maripaludis
How do we construct the framework
���7
Methanococcus maripaludis
How do we construct the framework
���7
Methanococcus maripaludis Escherichia coli Homo sapiensArabidopsis thaliana
How do we construct the framework
���7
Methanococcus maripaludis Escherichia coli Homo sapiensArabidopsis thaliana
It can identify new features
���8
It can identify new features
���8
Increased emphasison metabolite roles
It can identify new features
���8
Increased emphasison metabolite roles
It can identify new features
���8
Increased emphasison metabolite roles
Putative metabolic‘devices’
We can use this network to revise our knowledge
���9
Methanococcus maripaludis
We can use this network to revise our knowledge
���9
Methanococcus maripaludis
We can use this network to revise our knowledge
���9
Methanococcus maripaludis
Helping to sort out the bigger picture
���10
!
• Define the global framework
• Curating organismal networks
• Finding intermediate structures
• Identify community structure
• Visualizing metabolism at depth
!
• Define the global framework
• Curating organismal networks
• Finding intermediate structures
• Identify community structure
• Visualizing metabolism at depth
Talk Outline
���11
!
• Curating organismal networks
How much of a need exists to correct databases?
���12
In the course of 1 year for 979 organisms in the Kyoto Encyclopedia of Genes and Genomes Database:
How much of a need exists to correct databases?
���12
In the course of 1 year for 979 organisms in the Kyoto Encyclopedia of Genes and Genomes Database:
• 88,000 metabolites have been added as annotations
How much of a need exists to correct databases?
���12
In the course of 1 year for 979 organisms in the Kyoto Encyclopedia of Genes and Genomes Database:
• 88,000 metabolites have been added as annotations
• 31,000 metabolites that were annotated have been removed
How much of a need exists to correct databases?
���12
In the course of 1 year for 979 organisms in the Kyoto Encyclopedia of Genes and Genomes Database:
• 88,000 metabolites have been added as annotations
• 31,000 metabolites that were annotated have been removed
• Resulting in an average of over 100 changes per organism
How much of a need exists to correct databases?
���12
How can we make predictions?
���13
For every reaction there is a set of enzyme sequences that we can compare to each organismal set of proteins
to see how well that reaction ‘fits’
How can we make predictions?
���13
For every reaction there is a set of enzyme sequences that we can compare to each organismal set of proteins
to see how well that reaction ‘fits’
Protein1Organism1
Protein2Organism1
Protein3Organism1
Protein4Organism1
Organism1proteins
How can we make predictions?
���13
For every reaction there is a set of enzyme sequences that we can compare to each organismal set of proteins
to see how well that reaction ‘fits’
Reaction1(Annotated)
Protein1Organism1
Protein2Organism1
Protein3Organism1
Protein4Organism1
Organism1proteins
How can we make predictions?
���13
For every reaction there is a set of enzyme sequences that we can compare to each organismal set of proteins
to see how well that reaction ‘fits’
Reaction1(Annotated)
Protein1Organism1
Protein2Organism1
Protein3Organism1
Protein4Organism1
Organism1proteins
Enzyme1Organism1
Enzyme1Organism2
Enzyme1Organism3
Enzyme1Organism4
Reaction1enzymes
How can we make predictions?
���14
Protein1Organism1
Protein2Organism1
Protein3Organism1
Protein4Organism1
Organism1proteins
Enzyme1Organism1
Enzyme1Organism2
Enzyme1Organism3
Enzyme1Organism4
Reaction1enzymes
How can we make predictions?
���14
Protein1Organism1
Protein2Organism1
Protein3Organism1
Protein4Organism1
Organism1proteins
Enzyme1Organism1
Enzyme1Organism2
Enzyme1Organism3
Enzyme1Organism4
Reaction1enzymes
How can we make predictions?
���14
Protein1Organism1
Protein2Organism1
Protein3Organism1
Protein4Organism1
Organism1proteins
Enzyme1Organism1
Enzyme1Organism2
Enzyme1Organism3
Enzyme1Organism4
Reaction1enzymes
Protein BLASTfor Enzyme Sequences
How can we make predictions?
���15
For every reaction there is a set of enzyme sequences that we can compare to each organismal set of proteins
to see how well that reaction ‘fits’
Reaction1(Annotated)
Protein1Organism1
Protein2Organism1
Protein3Organism1
Protein4Organism1
Organism1proteins
Enzyme1Organism1
Enzyme1Organism2
Enzyme1Organism3
Enzyme1Organism4
Reaction1enzymes
0.0
MatchE-values
10-3
10-45.0
10-2
How can we make predictions?
���16
For every reaction there is a set of enzyme sequences that we can compare to each organismal set of proteins
to see how well that reaction ‘fits’
Protein1Organism1
Protein2Organism1
Protein3Organism1
Protein4Organism1
Organism1proteins
Enzyme1Organism1
Enzyme1Organism2
Enzyme1Organism3
Enzyme1Organism4
Reaction1enzymes
0.0
MatchE-values
10-3
10-45.0
10-2
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ExcellentMatches
Frac
tion
of M
atch
es
PoorMatches
How can we make predictions?
���16
For every reaction there is a set of enzyme sequences that we can compare to each organismal set of proteins
to see how well that reaction ‘fits’
Reaction1(Annotated)
Reaction2(Unannotated)
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atch
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How can we make predictions?
���16
For every reaction there is a set of enzyme sequences that we can compare to each organismal set of proteins
to see how well that reaction ‘fits’
Reaction1(Annotated)
Reaction2(Unannotated)
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atch
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How can we make predictions?
���17
For every reaction there is a set of enzyme sequences that we can compare to each organismal set of proteins
to see how well that reaction ‘fits’
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atch
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How can we make predictions?
���17
For every reaction there is a set of enzyme sequences that we can compare to each organismal set of proteins
to see how well that reaction ‘fits’
Repeat this for all 3328 reactions using 5.94 million enzyme sequences in 873 organisms
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atch
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Are there real differences?
10-3
10-2
10-1
10-2 10-1 100Fraction of Hits
Fracti
on
of
Reacti
on
s
Annotated
���18
Are there real differences?
Unannotated
10-3
10-2
10-1
10-2 10-1 100Fraction of Hits
Fracti
on
of
Reacti
on
s
Annotated
���18
Picking an optimal threshold
���19
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Frac
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atch
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PoorMatches
Picking an optimal threshold
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Frac
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atch
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Picking an optimal threshold
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Frac
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atch
es
PoorMatches
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Acc
urac
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e D
isco
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Picking an optimal threshold
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atch
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urac
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How do we validate our results?
���20
• We have one starting dataset, metabolic networks from KEGG 2009
How do we validate our results?
���20
• We have one starting dataset, metabolic networks from KEGG 2009
• We have our predicted networks and its changes to this dataset (Predicted Changes)
How do we validate our results?
���20
• We have one starting dataset, metabolic networks from KEGG 2009
• We have our predicted networks and its changes to this dataset (Predicted Changes)
• I also have the entire KEGG dataset for 2 years following that date (KEGG Changes)
How do we validate our results?
���20
• We have one starting dataset, metabolic networks from KEGG 2009
• We have our predicted networks and its changes to this dataset (Predicted Changes)
• I also have the entire KEGG dataset for 2 years following that date (KEGG Changes)
• I also have other databases to use (FBA Reconstructions, Ma Zeng, Zeng)
How do we validate our results?
���20
• We have one starting dataset, metabolic networks from KEGG 2009
• We have our predicted networks and its changes to this dataset (Predicted Changes)
• I also have the entire KEGG dataset for 2 years following that date (KEGG Changes)
• I also have other databases to use (FBA Reconstructions, Ma Zeng, Zeng)
• So where’s my accuracy number?
How do we validate our results?
���20
Well, our test source isn’t perfect over time
���21
Well, our test source isn’t perfect over time
���21
And if we look across databases....
���22
And if we look across databases....
���22
So really, it’s more like “accuracy”
And if we look across databases....
���22
So really, it’s more like “accuracy”
But as an approximation we can use a consensus network
How to build a consensus network
���23
KEGG 2009 Zeng 2011 FBA
How to build a consensus network
���23
KEGG 2009 Zeng 2011 FBA
Consensus Network We use majority rule to make the
consensus network
How do the databases compare
���24
Global Network
How do the databases compare
���24
Global Network
What are we mispredicting?
���25
What are we mispredicting?
���26
What are we mispredicting?
���26
Reactions that we predict to exist but
are not in other databases are
primarily composed of reactions that are poorly understood, if
at all
But can we validate in another way?
���27
• Traditional validation is hamstrung by what we “know”
But can we validate in another way?
���27
• Traditional validation is hamstrung by what we “know”
• We can instead try to validate by assessing how well connected a metabolic network is, namely:
But can we validate in another way?
���27
• Traditional validation is hamstrung by what we “know”
• We can instead try to validate by assessing how well connected a metabolic network is, namely:
• Do we leave gaps between reactions when the organismal network is overlaid on the Res Potentia?
But can we validate in another way?
���27
• Traditional validation is hamstrung by what we “know”
• We can instead try to validate by assessing how well connected a metabolic network is, namely:
• Do we leave gaps between reactions when the organismal network is overlaid on the Res Potentia?
• When we remove reactions do we make more components than necessary, increasing the reliance on nutrient import?
But can we validate in another way?
���27
Validate by promoting connectedness
���28
We can test and see how the actual changes in the database do at completing and filling in gaps
in the networks
Validate by promoting connectedness
���28
We can test and see how the actual changes in the database do at completing and filling in gaps
in the networks
Validate by promoting connectedness
���28
Gap Size0.00
0.02
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Frac
tion
of G
aps
Fille
d KEGG ChangesRandom
1 2 3 4 5
Predicted Changes
We can test and see how the actual changes in the database do at completing and filling in gaps
in the networks
Validate by promoting connectedness
���28
Gap Size0.00
0.02
0.04
0.06
0.08
0.10
0.12
Frac
tion
of G
aps
Fille
d KEGG ChangesRandom
1 2 3 4 5
Predicted Changes
We can test and see how the actual changes in the database do at completing and filling in gaps
in the networks
Validate by promoting connectedness
���28
Gap Size0.00
0.02
0.04
0.06
0.08
0.10
0.12
Frac
tion
of G
aps
Fille
d KEGG ChangesRandom
1 2 3 4 5
Predicted Changes
We can test and see how the actual changes in the database do at completing and filling in gaps
in the networks
Validate by promoting connectedness
���28
Gap Size0.00
0.02
0.04
0.06
0.08
0.10
0.12
Frac
tion
of G
aps
Fille
d KEGG ChangesRandom
1 2 3 4 5
Predicted Changes
We can test and see how the actual changes in the database do at completing and filling in gaps
in the networks
Validate by promoting connectedness
���29
We can test and see how the actual changes in the database create gaps
Validate by promoting connectedness
���29
We can test and see how the actual changes in the database create gaps
Validate by promoting connectedness
���29
We can test and see how the actual changes in the database create gaps
Validate by promoting connectedness
���29
We can test and see how the actual changes in the database create gaps
-0.1 -0.06 -0.02 0.02 0.06 0.1
RPF PredictedDeletions
KEGG 2011Deletions
Relative fraction of removed reactionsthat create additional components
Validate by promoting connectedness
���29
We can test and see how the actual changes in the database create gaps
-0.1 -0.06 -0.02 0.02 0.06 0.1
RPF PredictedDeletions
KEGG 2011Deletions
Relative fraction of removed reactionsthat create additional components
We can also ‘type’ the current curation efforts
���30
0
2
4
6
8
10
10-2 10-1 100 101 102
AdditionsRemovals
Mo
de
l Org
an
ism
s
PredictionsKEGG Changes
More changesin KEGG
Fewer changesin KEGG
Nu
mb
er
of
Org
an
ism
s
We can also ‘type’ the current curation efforts
���30
0
2
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10-2 10-1 100 101 102
AdditionsRemovals
Mo
de
l Org
an
ism
s
PredictionsKEGG Changes
More changesin KEGG
Fewer changesin KEGG
Nu
mb
er
of
Org
an
ism
s
0100200300400500600700
All O
rg
an
ism
s
More changesin KEGG
Fewer changesin KEGG
10-2 10-1 100 101 102Predictions
KEGG Changes
!
• Define the global framework
• Curating organismal networks
• Finding intermediate structures
• Identify community structure
• Visualizing metabolism at depth
!
• Define the global framework
• Curating organismal networks
• Finding intermediate structures
• Identify community structure
• Visualizing metabolism at depth
Talk Outline
���31
!
• Finding intermediate structures
We typically examine local structure in two ways!
Using known pathways and reaction conversions
We typically examine local structure in two ways!
Using known pathways and reaction conversions
!
Using a priori defined structures
We typically examine local structure in two ways!
Using known pathways and reaction conversions
!
Using a priori defined structures
!
Both are predetermined functionally
We establish a profile for each reaction
���33
Reaction1(Annotated)
We establish a profile for each reaction
���33
Reaction1(Annotated)
!
For each reaction tested in an organism we know the
percentage of BLAST alignments that returned a ‘good’ result
We establish a profile for each reaction
���33
Reaction1(Annotated)
H. sapiens
fhits = 0.84
!
For each reaction tested in an organism we know the
percentage of BLAST alignments that returned a ‘good’ result
We establish a profile for each reaction
���33
Reaction1(Annotated)
H. sapiens
fhits = 0.84
!
For each reaction tested in an organism we know the
percentage of BLAST alignments that returned a ‘good’ result
E. colifhits = 0.6
S. pombefhits = 0.7 . . .
We establish a profile for each reaction
���33
Reaction1(Annotated)
H. sapiens
fhits = 0.84
!
For each reaction tested in an organism we know the
percentage of BLAST alignments that returned a ‘good’ result
E. colifhits = 0.6
S. pombefhits = 0.7 . . .
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CDF
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We pick every edge and try to “grow” a device
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Reaction1(Annotated)
We pick every edge and try to “grow” a device
���34
Reaction1(Annotated)
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We pick every edge and try to “grow” a device
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Reaction1(Annotated)
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We pick every edge and try to “grow” a device
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Reaction1(Annotated)
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We pick every edge and try to “grow” a device
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Reaction1(Annotated)
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CDF
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D
We pick every edge and try to “grow” a device
���34
Reaction1(Annotated)
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CDF
0.0 0.5 1.0fhits
D
Reject the growth of a
device
We pick every edge and try to “grow” a device
���34
Reaction1(Annotated)
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1.0
CDF
0.0 0.5 1.0fhits
D
Reject the growth of a
device
We pick every edge and try to “grow” a device
���34
Reaction1(Annotated)
0.0
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1.0
CDF
0.0 0.5 1.0fhits
D
Reject the growth of a
device
0.0
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1.0CDF
0.0 0.5 1.0fhits
We pick every edge and try to “grow” a device
���34
Reaction1(Annotated)
0.0
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1.0
CDF
0.0 0.5 1.0fhits
D
Reject the growth of a
device
0.0
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1.0CDF
0.0 0.5 1.0fhits
We pick every edge and try to “grow” a device
���34
Reaction1(Annotated)
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CDF
0.0 0.5 1.0fhits
D
Reject the growth of a
device
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1.0CDF
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Accept growth
What are general characteristics of what we found?
���35
We find 230 devices using this methodology, spanning in size from 3 to 6 compounds
Some are small linear chains
What are general characteristics of what we found?
���35
We find 230 devices using this methodology, spanning in size from 3 to 6 compounds
Some are small linear chains
m32-C03785
m32-C00111
m18-C06893
m43-C00062
m48-C01201
m48-C00301
m43-C03296
Some are small linear chains
What are general characteristics of what we found?
���35
We find 230 devices using this methodology, spanning in size from 3 to 6 compounds
Some are small linear chains
m32-C03785
m32-C00111
m18-C06893
m43-C00062
m48-C01201
m48-C00301
m43-C03296
Others branch
Some are small linear chains
m22-C05956
m22-C00696
m22-C00584
m22-C00427
m32-C06140
m32-C06141
m32-C04927
m32-C06134
m32-C06139
m32-C06138
Is there any significance to these devices?
���36
Some are small linear chains
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Is there any significance to these devices?
���36
Some are small linear chains
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Devices
Is there any significance to these devices?
���37
Some are small linear chains
0.0
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Is there any significance to these devices?
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Some are small linear chains
0.0
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DevicesGlobal
R1
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!
• Define the global framework
• Curating organismal networks
• Finding intermediate structures
• Identify community structure
• Visualizing metabolism at depth
!
• Define the global framework
• Curating organismal networks
• Finding intermediate structures
• Identify community structure
• Visualizing metabolism at depth
Talk Outline
���38
!
• Identify community structure
Community detection is a heuristic solution
���39
Community detection is a heuristic solution
• Modularity Landscape Surveying (MLS) 64 communities
3030
282828282929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929
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Mod
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0
20
40
60
80
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tion
���39
Community detection is a heuristic solution
• Modularity Landscape Surveying (MLS) 64 communities
• MLS with simulated annealing (SA) for structure extraction13 communities
0
20
40
60
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100
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tion
11111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111
101010101010101010101010101010101010101010101010101010101010101010101010101010101010
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���39
Community detection is a heuristic solution
• Modularity Landscape Surveying (MLS) 64 communities
• MLS with simulated annealing (SA) for structure extraction13 communities
• SA Modularity Maximization (100 runs)Min: 16 communitiesMax: 24 communities
���39
Why not just start over entirely?
���40
Why not just start over entirely?
• Time
���40
Why not just start over entirely?
• Time
• Modularity Landscape Run-time for the Res Potentia network is 40 days
���40
Why not just start over entirely?
• Time
• Modularity Landscape Run-time for the Res Potentia network is 40 days
• Changing the structure extraction to simulated annealing increases the time dramatically (>60 days)
���40
Why not just start over entirely?
• Time
• Modularity Landscape Run-time for the Res Potentia network is 40 days
• Changing the structure extraction to simulated annealing increases the time dramatically (>60 days)
• Final evaluations and comparisons of structure
���40
What can we make final determinations on?
���41
What can we make final determinations on?
• Qualitative
���41
What can we make final determinations on?
• Qualitative
• Distribution of conservation values
���41
What can we make final determinations on?
• Qualitative
• Distribution of conservation values
• Pathway/functional conservation
���41
What can we make final determinations on?
• Qualitative
• Distribution of conservation values
• Pathway/functional conservation
• Quantitative
���41
What can we make final determinations on?
• Qualitative
• Distribution of conservation values
• Pathway/functional conservation
• Quantitative
• Modularity
���41
What can we make final determinations on?
• Qualitative
• Distribution of conservation values
• Pathway/functional conservation
• Quantitative
• Modularity
• Matrix cost
���41
How can we make improvements?
���42
How can we make improvements?
• Work on moving the communities themselves instead of the nodes
���42
How can we make improvements?
• Work on moving the communities themselves instead of the nodes
• With only one type of move proposed: Merge two communities
���42
How can we make improvements?
• Work on moving the communities themselves instead of the nodes
• With only one type of move proposed: Merge two communities
• Start with communities that have only one link
���42
How can we make improvements?
• Work on moving the communities themselves instead of the nodes
• With only one type of move proposed: Merge two communities
• Start with communities that have only one link
• Proceed to attempt merges of smaller communities
���42
How can we make improvements?
• Work on moving the communities themselves instead of the nodes
• With only one type of move proposed: Merge two communities
• Start with communities that have only one link
• Proceed to attempt merges of smaller communities
• Evaluate each merge with modularity and matrix costs
���42
How can we make improvements?
• Work on moving the communities themselves instead of the nodes
• With only one type of move proposed: Merge two communities
• Start with communities that have only one link
• Proceed to attempt merges of smaller communities
• Evaluate each merge with modularity and matrix costs
• Make sure that one community continually maps to one network component
���42
Iteration 1, What do we select?
3030
282828282929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929
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20
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���43
-0.003 -0.0025 -0.002 -0.0015 -0.001 -0.0005 0 0.0005Normalized Additional Modularity Cost
0
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Accept Changes
���44
What does one iteration of merging do?
3030
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1717171717171717171717171717171717171717171717171717171717171717171717
15151515
3232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232
5858585858
1111111111
101010
393939393939
38383838
595959595959595959595959
2222222222222222222222222222222222222222222222222222222222222222222222
1414141414141414141414
1616161616
19191919191919191919191919191919
54
31
5656
51515151515151
3636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636
53535353535353535353535353535353
52525252
333333333333333333333333333333333333333333
55555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555
3737373737
47
5757575757575757575757
5050505050505050
���45
What does one iteration of merging do?
3030
28282828292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929
606060606060606060
626262626262626262626262
64646464646464
35353535353535
343434
242424242424242424242424242424242424242424242424
2525252525252525252525252626262626262626
272727272727
2020
212121
4848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848
494949494949
4646464646
47
444444444444
454545454545 424242424242424242424242424242424242424242424242
434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434040
4141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141 111111
0000000
33335555555
4444444
7777777777777777777777777777777777
1414141414141414141414
9999999999999999999999999999888888888888888
13
1212121212
15151515
323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232
585858
1111111111
101010
393939393939
38383838
595959595959595959595959
2222222222222222222222222222222222222222222222222222222222222222222222
16161616161616161616161616161616161616161616161616161616161616161616161616161616
19191919191919191919191919191919
54
31
2323232323232323232323232323232323232323232323232323232323
51515151515151
36363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636
53535353535353535353535353535353
52525252
333333333333333333333333333333333333333333
555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555
3737373737
181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818185757575757575757575757
5050505050505050
3030
282828282929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929
606060
616161616161
626262626262
636363636363
64646464646464
35353535353535
343434
242424242424242424242424242424242424242424242424
2525252525252525252525252626262626262626
27272727
2020
212121
4848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848
494949494949
4646464646
2323232323232323232323232323232323232323232323232323232323
44444444444444
454545454545 424242424242424242424242424242424242424242424242
43434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343404040
41414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141 111
0000000
3333222
5555555
44
7777777777777777777777777777777777
66666
9999999999999999999999999999888888888888888
181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818
13
1212121212
1717171717171717171717171717171717171717171717171717171717171717171717
15151515
3232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232
5858585858
1111111111
101010
393939393939
38383838
595959595959595959595959
2222222222222222222222222222222222222222222222222222222222222222222222
1414141414141414141414
1616161616
19191919191919191919191919191919
54
31
5656
51515151515151
3636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636
53535353535353535353535353535353
52525252
333333333333333333333333333333333333333333
55555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555
3737373737
47
5757575757575757575757
5050505050505050
���45
How do we pick more complicated targets?
���46
Modules with a small degree
How do we pick more complicated targets?
���46
Are complicated moves worthwhile?
-0.006 -0.005 -0.004 -0.003 -0.002 -0.001 0 0.001Normalized Additional Modularity Cost
0
0.005
0.01
0.015
0.02
0.025
Nor
mal
ized
Add
ition
al M
atrix
Cos
t
���47
We can also improve at the node level
���48
We can also improve at the node level
The network is supposed to focus on the flow of mass through reactions
���48
We can also improve at the node level
The network is supposed to focus on the flow of mass through reactions
But association and disassociation reactions don’t follow this strictly
���48
We can also improve at the node level
The network is supposed to focus on the flow of mass through reactions
But association and disassociation reactions don’t follow this strictly
Metabolitea Metabolitea’ + Metabolitea’’
���48
We can also improve at the node level
The network is supposed to focus on the flow of mass through reactions
But association and disassociation reactions don’t follow this strictly
Metabolitea Metabolitea’ + Metabolitea’’
Main Reaction Pairs
���48
We can also improve at the node level
The network is supposed to focus on the flow of mass through reactions
But association and disassociation reactions don’t follow this strictly
Metabolitea Metabolitea’ + Metabolitea’’
Main Reaction Pairs
���48
We can also improve at the node level
The network is supposed to focus on the flow of mass through reactions
But association and disassociation reactions don’t follow this strictly
Metabolitea Metabolitea’ + Metabolitea’’
Main Reaction Pairs
MetaboliteaMetabolitea’ Metabolitea’’
���48
Is this really a problem?
���49
Is this really a problem?
Not that much, but it can interfere when these are the reactions that connect between modules.
���49
Is this really a problem?
Not that much, but it can interfere when these are the reactions that connect between modules.
���49
What is the end result of all these moves?
4242424242424242424242424242424242
2929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929
626262626262626262626262
24242424242424242424242424242424
25252525252525
212121
2222222222222222222222222222222222222222222222222222222222222222222222
2323232323232323232323232323232323232323232323232323232323
28282828
43434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343
414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141
11111111
000000
7777777777777777777777777777777777777777777777777777777777
888888888888888
1313131313131313131313131313131313131313131313131313131313
1414141414141414141414
393939393939393939393939393939393939393939393939393939393939393939393939
595959595959595959595959595959595959595959595959595959595959
484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848484848
16161616161616161616161616161616161616161616161616161616161616161616161616161616
19191919191919191919191919191919
181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818181818
5757575757575757575757
3737373737
3636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636363636
53535353535353535353535353535353
34343434343434343434
555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555
323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232323232
���50
What is the end result of all these moves?
Reduction of modules from 64 to 30
4242424242424242424242424242424242
2929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929292929
626262626262626262626262
24242424242424242424242424242424
25252525252525
212121
2222222222222222222222222222222222222222222222222222222222222222222222
2323232323232323232323232323232323232323232323232323232323
28282828
43434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343434343
414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141414141
11111111
000000
7777777777777777777777777777777777777777777777777777777777
888888888888888
1313131313131313131313131313131313131313131313131313131313
1414141414141414141414
393939393939393939393939393939393939393939393939393939393939393939393939
595959595959595959595959595959595959595959595959595959595959
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Modularity: Matrix Cost: ���50
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• Define the global framework
• Curating organismal networks
• Finding intermediate structures
• Identify community structure
• Visualizing metabolism at depth
!
• Define the global framework
• Curating organismal networks
• Finding intermediate structures
• Identify community structure
• Visualizing metabolism at depth
Talk Outline
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!
• Visualizing metabolism at depth
How do we currently look at metabolism?
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What are the other ways researchers try?
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What are the other ways researchers try?
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How do we interact with these graphs?
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How do we interact with these graphs?
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How do we interact with these graphs?
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What am I proposing?
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What am I proposing?
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• Let’s share more than our raw data
What am I proposing?
���56
• Let’s share more than our raw data
• Make a visualization that allows for interaction with our data and analyses
What am I proposing?
���56
• Let’s share more than our raw data
• Make a visualization that allows for interaction with our data and analyses
• Make it freely available
MetExplore Workflows within a level
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Splash Page
MetExplore Workflows within a level
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Splash Page hover
MetExplore Workflows: Exploring deeper
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MetExplore Workflows: Exploring deeper
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click
MetExplore Workflows: Exploring deeper
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click
click
MetExplore Workflows: Moving across
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click
MetExplore Workflows: Moving across
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click
click
Wrapping up
• I have developed a framework to analyze cellular processes, we can:
• Predict organismal networks
• Assess curation efficacy
• Identify intermediate and global structure
• We also are able now to make visualizations that allow for graph traversal and exploration
Acknowledgements
• Luis Amaral
• Eric Weiss, Adilson Motter, Joshua Leonard
• Dan McClary, Erin Sawardecker, Pat McMullen, Laura Timmerman, Julia Poncela, Renee Robbins
With financial support from:
• Northwestern/NIH Biotechnology Training Grant
• Chicago Biomedical Consortium
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