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Project-team MAGNOME Inria Bordeaux - Sud-Ouest JOBIM 2013, July 1-4 Metabolic Model Generalization Anna Zhukova
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Metabolic Model Generalization

Jul 03, 2015

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JOBIM 2013, Toulouse
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Page 1: Metabolic Model Generalization

Project-teamMAGNOMEInria Bordeaux - Sud-Ouest

JOBIM 2013, July 1-4

Metabolic Model Generalization

Anna Zhukova

Page 2: Metabolic Model Generalization

Where's Wally ?

Page 3: Metabolic Model Generalization

Where are missing reactions ?

(The fi gure is produced using the Tulip graph visualization tool.)

Page 4: Metabolic Model Generalization

Where are missing reactions ?

(The fi gure is produced using the Tulip graph visualization tool.)

Page 5: Metabolic Model Generalization

Where are missing reactions ?

(The fi gure is produced using the Tulip graph visualization tool.)

Page 6: Metabolic Model Generalization

Where are missing reactions ?

MODEL1111190000 

Loira et al., 2012 

Metabolic Network of Y. lipolytica

(peroxisome)

(53 - 6) reactions

(The fi gure is produced using the Tulip graph visualization tool.)

Page 7: Metabolic Model Generalization

Where are missing reactions ?

(The fi gure is produced using the Tulip graph visualization tool.)

Page 8: Metabolic Model Generalization

3-hydroxyacyl dehydrase ! Not that easy ?

(The fi gure is produced using the Tulip graph visualization tool.)

Page 9: Metabolic Model Generalization

Model inference and refinement

Page 10: Metabolic Model Generalization

Let's generalize !

(The fi gure is produced using the Tulip graph visualization tool.)

Page 11: Metabolic Model Generalization

Let's generalize : ubiquitous species !

(The fi gure is produced using the Tulip graph visualization tool.)

Page 12: Metabolic Model Generalization

Let's generalize !

(The fi gure is produced using the Tulip graph visualization tool.)

Page 13: Metabolic Model Generalization

Let's generalize : hydroxy fatty acyl-CoA !

(The fi gure is produced using the Tulip graph visualization tool.)

Page 14: Metabolic Model Generalization

Let's generalize !

(The fi gure is produced using the Tulip graph visualization tool.)

Page 15: Metabolic Model Generalization

Let's generalize : dehydroacyl-CoA !

(The fi gure is produced using the Tulip graph visualization tool.)

Page 16: Metabolic Model Generalization

Let's generalize !

(The fi gure is produced using the Tulip graph visualization tool.)

Page 17: Metabolic Model Generalization

Let's generalize : 3-hydroxyacyl dehydratase !

(The fi gure is produced using the Tulip graph visualization tool.)

Page 18: Metabolic Model Generalization

Let's generalize !

(The fi gure is produced using the Tulip graph visualization tool.)

Page 19: Metabolic Model Generalization

Let's factor !

(The fi gure is produced using the Tulip graph visualization tool.)

Page 20: Metabolic Model Generalization

Let's improve the layout a bit...

(The fi gure is produced using the Tulip graph visualization tool.)

Page 21: Metabolic Model Generalization

So, where's Wally (aka 3-hydroxyacyl-CoA dehydratase) ?

(The fi gure is produced using the Tulip graph visualization tool.)

Page 22: Metabolic Model Generalization

Some technical details...

Page 23: Metabolic Model Generalization

Some technical details...

M = (S, Sub, R) – model

Page 24: Metabolic Model Generalization

Some technical details...

M = (S, Sub, R) – model

S = {s1, ..., s

n} – species set

/including /

Sub – ubiquitous species set

Page 25: Metabolic Model Generalization

Some technical details...

M = (S, Sub, R) – model

S = {s1, ..., s

n} – species set

/including /

Sub – ubiquitous species set

R = {r1, ..., r

n} – reaction set

r = (S(react), S(prod)) – reaction/all the species are distinct (*)/

Page 26: Metabolic Model Generalization

Some technical details...

M = (S, Sub, R) – model

S = {s1, ..., s

n} – species set

/including /

Sub – ubiquitous species set

R = {r1, ..., r

n} – reaction set

r = (S(react), S(prod)) – reaction/all the species are distinct (*)/

Page 27: Metabolic Model Generalization

Some technical details...

M = (S, Sub, R) – model

S = {s1, ..., s

n} – species set

/including /

Sub – ubiquitous species set

R = {r1, ..., r

n} – reaction set

r = (S(react), S(prod)) – reaction/all the species are distinct (*)/

stoichiometry = 2

Page 28: Metabolic Model Generalization

Some technical details...

Choose equivalence operation ~ :[s]~ = {s

i | s

i ~ s} – generalized species

[s(ub)]~ = {s(ub)} – (trivial) generalized ub. sp.

M = (S, Sub, R) – model

S = {s1, ..., s

n} – species set

/including /

Sub – ubiquitous species set

R = {r1, ..., r

n} – reaction set

r = (S(react), S(prod)) – reaction/all the species are distinct (*)/

Page 29: Metabolic Model Generalization

Some technical details...

Choose equivalence operation ~ :[s]~ = {s

i | s

i ~ s} – generalized species

[s(ub)]~ = {s(ub)} – (trivial) generalized ub. sp.[r]~ = (S([react]), S([prod])) =

/all the generalized species are distinct (*)/

= {ri | r

i ~ r} – generalized reaction

M = (S, Sub, R) – model

S = {s1, ..., s

n} – species set

/including /

Sub – ubiquitous species set

R = {r1, ..., r

n} – reaction set

r = (S(react), S(prod)) – reaction/all the species are distinct (*)/

Page 30: Metabolic Model Generalization

Some technical details...

Choose equivalence operation ~ :[s]~ = {s

i | s

i ~ s} – generalized species

[s(ub)]~ = {s(ub)} – (trivial) generalized ub. sp.[r]~ = (S([react]), S([prod])) =

/all the generalized species are distinct (*)/

= {ri | r

i ~ r} – generalized reaction

M = (S, Sub, R) – model

S = {s1, ..., s

n} – species set

/including /

Sub – ubiquitous species set

R = {r1, ..., r

n} – reaction set

r = (S(react), S(prod)) – reaction/all the species are distinct (*)/

Page 31: Metabolic Model Generalization

Some technical details...

Choose equivalence operation ~ :[s]~ = {s

i | s

i ~ s} – generalized species

[s(ub)]~ = {s(ub)} – (trivial) generalized ub. sp.[r]~ = (S([react]), S([prod])) =

/all the generalized species are distinct (*)/

= {ri | r

i ~ r} – generalized reaction

M = (S, Sub, R) – model

S = {s1, ..., s

n} – species set

/including /

Sub – ubiquitous species set

R = {r1, ..., r

n} – reaction set

r = (S(react), S(prod)) – reaction/all the species are distinct (*)/

Page 32: Metabolic Model Generalization

Some technical details...

Choose equivalence operation ~ :[s]~ = {s

i | s

i ~ s} – generalized species

[s(ub)]~ = {s(ub)} – (trivial) generalized ub. sp.[r]~ = (S([react]), S([prod])) =

/all the generalized species are distinct (*)/

= {ri | r

i ~ r} – generalized reaction

M = (S, Sub, R) – model

S = {s1, ..., s

n} – species set

/including /

Sub – ubiquitous species set

R = {r1, ..., r

n} – reaction set

r = (S(react), S(prod)) – reaction/all the species are distinct (*)/

Page 33: Metabolic Model Generalization

Some technical details...

Choose equivalence operation ~ :[s]~ = {s

i | s

i ~ s} – generalized species

[s(ub)]~ = {s(ub)} – (trivial) generalized ub. sp.[r]~ = (S([react]), S([prod])) =

/all the generalized species are distinct (*)/

= {ri | r

i ~ r} – generalized reaction

M = (S, Sub, R) – model

S = {s1, ..., s

n} – species set

/including /

Sub – ubiquitous species set

R = {r1, ..., r

n} – reaction set

r = (S(react), S(prod)) – reaction/all the species are distinct (*)/

Page 34: Metabolic Model Generalization

Some technical details...

Choose equivalence operation ~ :[s]~ = {s

i | s

i ~ s} – quotient species

[s(ub)]~ = {s(ub)} – (trivial) quotient ub. sp.[r]~ = (S([react]), S([prod])) =

/all the quotient species are distinct (*)/

= {ri | r

i ~ r} – quotient reaction

S/~ = {[s1], ..., [s

n]} – quotient species set

R/~ = {[r1], ..., [r

n]} – quotient reaction set

M/~ = (S/~, R/~) – generalized model

M = (S, Sub, R) – model

S = {s1, ..., s

n} – species set

/including /

Sub – ubiquitous species set

R = {r1, ..., r

n} – reaction set

r = (S(react), S(prod)) – reaction/all the species are distinct (*)/

Page 35: Metabolic Model Generalization

Some technical details...

Choose equivalence operation ~ :[s]~ = {s

i | s

i ~ s} – generalized species

[s(ub)]~ = {s(ub)} – (trivial) generalized ub. sp.[r]~ = (S([react]), S([prod])) =

/all the generalized species are distinct (*)/

= {ri | r

i ~ r} – generalized reaction

S/~ = {[s1], ..., [s

n]} – generalized species set

R/~ = {[r1], ..., [r

n]} – generalized reaction set

M/~ = (S/~, R/~) – generalized model

Problem: Given a model M = (S, Sub, R), find an equivalence operation ~ that obeys the stoichiometry

preserving restriction (*), and minimizes the number of generalized reactions #R/~. Among such

equivalence operations choose the one that defines the maximal number of generalized species #S/~.  

M = (S, Sub, R) – model

S = {s1, ..., s

n} – species set

/including /

Sub – ubiquitous species set

R = {r1, ..., r

n} – reaction set

r = (S(react), S(prod)) – reaction/all the species are distinct (*)/

Page 36: Metabolic Model Generalization

Algorithm

Problem: Given a model M = (S, Sub, R), find an equivalence operation ~ that obeys the stoichiometry

preserving restriction (*), and minimizes the number of generalized reactions #R/~. Among such

equivalence operations choose the one that defines the maximal number of generalized species #S/~.  

Page 37: Metabolic Model Generalization

Algorithm

1. Define ~0

• [s(ub)]~0 = {s(ub)} – (trivial) generalized ub. sp.• [s]~0 = S\S

ub – generalized specific species

s1 ~ s

2 and do not participate in any equivalent reactions, then split [s

1]~0c

Problem: Given a model M = (S, Sub, R), find an equivalence operation ~ that obeys the stoichiometry

preserving restriction (*), and minimizes the number of generalized reactions #R/~. Among such

equivalence operations choose the one that defines the maximal number of generalized species #S/~.  

Page 38: Metabolic Model Generalization

Algorithm

1. Define ~0

• [s(ub)]~0 = {s(ub)} – (trivial) generalized ub. sp.• [s]~0 = S\S

ub – generalized specific species

s1 ~ s

2 and do not participate in any equivalent reactions, then split [s

1]~0c

Problem: Given a model M = (S, Sub, R), find an equivalence operation ~ that obeys the stoichiometry

preserving restriction (*), and minimizes the number of generalized reactions #R/~. Among such

equivalence operations choose the one that defines the maximal number of generalized species #S/~.  

Page 39: Metabolic Model Generalization

Algorithm

1. Define ~0

2. Preserve stoichiometry

Problem: Given a model M = (S, Sub, R), find an equivalence operation ~ that obeys the stoichiometry

preserving restriction (*), and minimizes the number of generalized reactions #R/~. Among such

equivalence operations choose the one that defines the maximal number of generalized species #S/~.  

Page 40: Metabolic Model Generalization

Algorithm

1. Define ~0

2. Preserve stoichiometry

Exact Set Cover Problem(NP-complete)

Greedy algorithm

Problem: Given a model M = (S, Sub, R), find an equivalence operation ~ that obeys the stoichiometry

preserving restriction (*), and minimizes the number of generalized reactions #R/~. Among such

equivalence operations choose the one that defines the maximal number of generalized species #S/~.  

Page 41: Metabolic Model Generalization

Algorithm

1. Define ~0

2. Preserve stoichiometry

Exact Set Cover Problem (NP-complete)Greedy Algorithm

s1 ~ s

2 and do not participate in any equivalent reactions, then split [s

1]~0c

Exact Set Cover Problem(NP-complete)

Greedy algorithm

Problem: Given a model M = (S, Sub, R), find an equivalence operation ~ that obeys the stoichiometry

preserving restriction (*), and minimizes the number of generalized reactions #R/~. Among such

equivalence operations choose the one that defines the maximal number of generalized species #S/~.  

Page 42: Metabolic Model Generalization

Algorithm

1. Define ~0

2. Preserve stoichiometry

Exact Set Cover Problem (NP-complete)Greedy Algorithm

s1 ~ s

2 and do not participate in any equivalent reactions, then split [s

1]~0c

Problem: Given a model M = (S, Sub, R), find an equivalence operation ~ that obeys the stoichiometry

preserving restriction (*), and minimizes the number of generalized reactions #R/~. Among such

equivalence operations choose the one that defines the maximal number of generalized species #S/~.  

Page 43: Metabolic Model Generalization

Algorithm

1. Define ~0

2. Preserve stoichiometry

Exact Set Cover Problem (NP-complete)Greedy Algorithm

s1 ~ s

2 and do not participate in any equivalent reactions, then split [s

1]~0c

Exact Set Cover Problem(NP-complete)

Greedy algorithm

Problem: Given a model M = (S, Sub, R), find an equivalence operation ~ that obeys the stoichiometry

preserving restriction (*), and minimizes the number of generalized reactions #R/~. Among such

equivalence operations choose the one that defines the maximal number of generalized species #S/~.  

Page 44: Metabolic Model Generalization

Algorithm

1. Define ~0

2. Preserve stoichiometry

3. Maximize generalized species numberreactions, then split [s1]~0c

Problem: Given a model M = (S, Sub, R), find an equivalence operation ~ that obeys the stoichiometry

preserving restriction (*), and minimizes the number of generalized reactions #R/~. Among such

equivalence operations choose the one that defines the maximal number of generalized species #S/~.  

Page 45: Metabolic Model Generalization

Algorithm

1. Define ~0

2. Preserve stoichiometry

3. Maximize generalized species numberreactions, then split [s1]~0c

Problem: Given a model M = (S, Sub, R), find an equivalence operation ~ that obeys the stoichiometry

preserving restriction (*), and minimizes the number of generalized reactions #R/~. Among such

equivalence operations choose the one that defines the maximal number of generalized species #S/~.  

Page 46: Metabolic Model Generalization

53 → 15

Page 47: Metabolic Model Generalization

Acknowledgements

Magnome Team, Inria Bordeaux, France

David James ShermanPascal DurrensFlorian LajusWitold DyrkaRazanne Issa

Page 48: Metabolic Model Generalization

Acknowledgements

Magnome Team, Inria Bordeaux, France

David James ShermanPascal DurrensFlorian LajusWitold DyrkaRazanne Issa

Center for Genome Regulation and CIRIC-InriaSantiago, Chile

Nicolás Loira

Page 49: Metabolic Model Generalization

Acknowledgements

Magnome Team, Inria Bordeaux, France

David James ShermanPascal DurrensFlorian LajusWitold DyrkaRazanne Issa

Center for Genome Regulation and CIRIC-InriaSantiago, Chile

Nicolás Loira

L'institut MicalisGrignon, France

Stéphanie MichelyJean-Marc Nicaud

Page 50: Metabolic Model Generalization

Acknowledgements

Magnome Team, Inria Bordeaux, France

David James ShermanPascal DurrensFlorian LajusWitold DyrkaRazanne Issa

Center for Genome Regulation and CIRIC-InriaSantiago, Chile

Nicolás Loira

L'institut MicalisGrignon, France

Stéphanie MichelyJean-Marc Nicaud

LaBRI Bordeaux, France

Antoine LambertRomain Bourqui

Page 51: Metabolic Model Generalization

Acknowledgements

Magnome Team, Inria Bordeaux, France

David James ShermanPascal DurrensFlorian LajusWitold DyrkaRazanne Issa

Center for Genome Regulation and CIRIC-InriaSantiago, Chile

Nicolás Loira

L'institut MicalisGrignon, France

Stéphanie MichelyJean-Marc Nicaud

LaBRI Bordeaux, France

Antoine LambertRomain Bourqui

findwally.co.ukLondon, UK

Martin HandfordWally

Page 52: Metabolic Model Generalization

Thank you!