ilp 2014 - nonmonotonic learning in large biological network
TRANSCRIPT
Nonmonotonic Learningin Large Biological Networks
Stefano Bragaglia, Oliver [email protected], [email protected]
Department of Computer ScienceUniversity of Bristol
14-17/09/2014 ILP '14, Nancy 1
• New open source XHAIL implementation
• Study of scalability on Biological Networks
• Found mistake in genome-scale network
14-17/09/2014 ILP '14, Nancy 2
XHAIL
• Nonmonotonic ILP – normal (extended) logic programs
– abductive, deductive, inductive
• Prototype (2006)
– ASP-based (lparse/smodels)
– Prolog wrapper (SWI-Prolog)
– Not defeasible
– Not
• Metabolic Network Revision (ILP 09)
– AAA model (~30 reactions)
– Pathway-specific model
• Non– normal
– Abductive
• Current application– ASP-based (gringo/clasp)
– Java wrapper (Java 8)
– Defeasible (language bias)
– Open source
• Metabolic Network Revision
– ABER model (1100+ reactions)
– Whole-organism model
14-17/09/2014 ILP '14, Nancy 3
XHAIL
• Nonmonotonic ILP – normal (extended) logic programs
– abductive, deductive, inductive
• Prototype (2006)
– ASP-based (lparse/smodels)
– Prolog wrapper (SWI-Prolog)
– Not defeasible
– Not
• Metabolic Network Revision (ILP 09)
– AAA model (~30 reactions)
– Pathway-specific model
• Non– normal
– Abductive
• Current application– ASP-based (gringo/clasp)
– Java wrapper (Java 8)
– Defeasible (language bias)
– Open source http://github.com/cathexis-bris-ac-uk/XHAIL
• Metabolic Network Revision
– ABER model (1100+ reactions)
– Whole-organism model
14-17/09/2014 ILP '14, Nancy 4
Approach Overview
14-17/09/2014 ILP '14, Nancy 5
modes
hypotheses
background
medium
cytosol
C00078
end
C00079
C00082
C00279
I00279
C00631
I00631
start
C00279
2.5.1.54
C00631
4.2.1.11
C00001
C00074
2.5.1.19C00009
C04691
4.2.3.4
C00944
4.2.1.10
C02637
?
C02652
1.1.1.25
C00000
C00006
C00493
C000051.3.1.13
2.7.1.71
C00002
C00008
C03175C012694.2.3.5
C00251
4.1.3.27
5.4.99.5
C00014
C00022
C00108
C00025
2.4.2.18
C00064
2.6.1.7
C00013
C04302
C00119
5.3.1.24
C01302
4.1.1.48
C00011
C03506
4.2.1.20
C00065
C00078
C00661
C00463
I00078
C002544.2.1.51
C00003C00004
C00166
C01179
C00026
C00079
C00082
I00079
I00082
XHAIL
#modeh inhib(+e, $m, $d).#modeb nutr(+e, $m, ext).#example not growth(2, 1).
react(5, [C02], [C05]).
meta(C05).obs_growth(2,1).
in_comp(Exp,Meta,Comp,Day) :-
s_comp(Meta,Comp).
inhib(V1, 10, 1) :-nutr(V1, "C08", ext), nutr(V1, "C06", ext), exp (V1).
evidences
Approach Overview
14-17/09/2014 ILP '14, Nancy 6
modes
newXHAIL
react(5, [C02], [C05]).
meta(C05).obs_growth(2,1).
background
hypotheses
inhib(V1, 10, 1) :-nutr(V1, "C08", ext), nutr(V1, "C06", ext), exp (V1).
:1 =3.:1 =2.
=4.
#modeh inhib(+e, $m, $d)#modeb nutr(+e, $m, ext)#example not growth(2, 1)
evidences
Model Revision
% Task A: YER090W as enzyme complex in 4.1.3.27
knockout(1, "YER090W").
#modeh component($orf, $enzID) :1 =3.
#example not predicted_growth(1, 1) =4.
knockout(2, "YER090W").
additional_nutrient(2, "C00108", medium).
#example predicted_growth(2, 1) =4.
H: component("YER090W", 54).
14-17/09/2014 ILP '14, Nancy 7
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C00008
C00002
YDR127W
2.7.1.71
C00009
YDR127W
4.2.1.10
YDR127W
4.2.3.4
4.2.1.11 YGR254W YHR174W
YMR323W
C00074
C00065
C00118
C00078
C03506
C04302
YDR007W
5.3.1.24
YGL026C
4.2.1.20
C00119
C00013
C01302
C00011
YKL211C
4.1.1.48
YDR354W
2.4.2.18
C00944
C02637
C01269
C00009
C03175
C00009
YGL148W 4.2.3.5
YDR127W
2.5.1.19
C04691
C00009
YBR249C YDR035W
2.5.1.54
YDR127W
1.1.1.25
C00005 C00006
C00493
YBR166C 1.3.1.13
C00006
C00005
YNL316C 4.2.1.51
C00011 C00011
YPR060C 5.4.99.5
C00254
C01179
C00082
C00025
C00026
YHR137W YGL202W
2.6.1.1
C00025
C00079
YHR137W YGL202W
2.6.1.7
C00166
C00026
C00251
C00279 C00631
C00108
C00064 C00022 C00025
YER090W YKL211C + YER090W
4.1.3.27
TYROSINE PHENYLALANINE
D-ERYTHROSE-4- PHOSPHATE
GLYCERATE-2- PHOSPHATE
Anthranilate
C00065
C00001
C00463
Indole
TRYPTOPHAN
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--
Model Revision
% Task B: C00082 inhibits YBR249C in 2.5.1.54
knockout(3, "YDR035W").
additional_nutrient(3, "C00082", medium).
#example not predicted_growth(3, 1) =4.
#modeh inhibitor($enzID, $meta, cytosol) :1 =2.
experiment(4).
additional_nutrient(4, "C00082", medium).
#example predicted_growth(4, 1) =4.
H: inhibitor(25, "C00082", cytosol).
14-17/09/2014 ILP '14, Nancy 8
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--
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-- --
--
C00008
C00002
YDR127W
2.7.1.71
C00009
YDR127W
4.2.1.10
YDR127W
4.2.3.4
4.2.1.11 YGR254W YHR174W
YMR323W
C00074
C00065
C00118
C00078
C03506
C04302
YDR007W
5.3.1.24
YGL026C
4.2.1.20
C00119
C00013
C01302
C00011
YKL211C
4.1.1.48
YDR354W
2.4.2.18
C00944
C02637
C01269
C00009
C03175
C00009
YGL148W 4.2.3.5
YDR127W
2.5.1.19
C04691
C00009
YBR249C YDR035W
2.5.1.54
YDR127W
1.1.1.25
C00005 C00006
C00493
YBR166C 1.3.1.13
C00006
C00005
YNL316C 4.2.1.51
C00011 C00011
YPR060C 5.4.99.5
C00254
C01179
C00082
C00025
C00026
YHR137W YGL202W
2.6.1.1
C00025
C00079
YHR137W YGL202W
2.6.1.7
C00166
C00026
C00251
C00279 C00631
C00108
C00064 C00022 C00025
YER090W YKL211C + YER090W
4.1.3.27
TYROSINE PHENYLALANINE
D-ERYTHROSE-4- PHOSPHATE
GLYCERATE-2- PHOSPHATE
Anthranilate
C00065
C00001
C00463
Indole
TRYPTOPHAN
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--
Model Revision
% Task C: C00463 contamination in 4.2.1.20
knockout(5, "YKL211C").
additional_nutrient(5, "C00463", medium).
#modeh include($reaction) :1 =3.
#example predicted_growth(5, 1) =4.
knockout(6, "YGl026C").
additional_nutrient(6, "C00463", medium).
#modeh catalyst($reaction, $enzID) :1 =3.
#example not predicted_growth(6, 1) =4.
knockout(7, "YKL211C").
observed_growth(false, 7, 1).
#example not predicted_growth(7, 1) =4.
H: catalyst(10910, 43).
include(10910).
14-17/09/2014 ILP '14, Nancy 9
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C00008
C00002
YDR127W
2.7.1.71
C00009
YDR127W
4.2.1.10
YDR127W
4.2.3.4
4.2.1.11 YGR254W YHR174W
YMR323W
C00074
C00065
C00118
C00078
C03506
C04302
YDR007W
5.3.1.24
YGL026C
4.2.1.20
C00119
C00013
C01302
C00011
YKL211C
4.1.1.48
YDR354W
2.4.2.18
C00944
C02637
C01269
C00009
C03175
C00009
YGL148W 4.2.3.5
YDR127W
2.5.1.19
C04691
C00009
YBR249C YDR035W
2.5.1.54
YDR127W
1.1.1.25
C00005 C00006
C00493
YBR166C 1.3.1.13
C00006
C00005
YNL316C 4.2.1.51
C00011 C00011
YPR060C 5.4.99.5
C00254
C01179
C00082
C00025
C00026
YHR137W YGL202W
2.6.1.1
C00025
C00079
YHR137W YGL202W
2.6.1.7
C00166
C00026
C00251
C00279 C00631
C00108
C00064 C00022 C00025
YER090W YKL211C + YER090W
4.1.3.27
TYROSINE PHENYLALANINE
D-ERYTHROSE-4- PHOSPHATE
GLYCERATE-2- PHOSPHATE
Anthranilate
C00065
C00001
C00463
Indole
TRYPTOPHAN
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--
Model Revision
% Task D: slow import of C00166, C01179
knockout(8, "YBR166C").
additional_nutrient(8, "C01179", medium).
#example not predicted_growth(8, 1) =4.
knockout(9, "YNL316C").
additional_nutrient(9, "C00166", medium).
#example not predicted_growth(9, 1) =4.
#example not predicted_growth(10, 1) =4.
#modeh inhibited(+ex, $enzID, $day) :2 =2.
H: inhibited(V1, 53, 1) :- experiment(V1).
inhibited(V1, 67, 1) :- experiment(V1).
14-17/09/2014 ILP '14, Nancy 10
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C00008
C00002
YDR127W
2.7.1.71
C00009
YDR127W
4.2.1.10
YDR127W
4.2.3.4
4.2.1.11 YGR254W YHR174W
YMR323W
C00074
C00065
C00118
C00078
C03506
C04302
YDR007W
5.3.1.24
YGL026C
4.2.1.20
C00119
C00013
C01302
C00011
YKL211C
4.1.1.48
YDR354W
2.4.2.18
C00944
C02637
C01269
C00009
C03175
C00009
YGL148W 4.2.3.5
YDR127W
2.5.1.19
C04691
C00009
YBR249C YDR035W
2.5.1.54
YDR127W
1.1.1.25
C00005 C00006
C00493
YBR166C 1.3.1.13
C00006
C00005
YNL316C 4.2.1.51
C00011 C00011
YPR060C 5.4.99.5
C00254
C01179
C00082
C00025
C00026
YHR137W YGL202W
2.6.1.1
C00025
C00079
YHR137W YGL202W
2.6.1.7
C00166
C00026
C00251
C00279 C00631
C00108
C00064 C00022 C00025
YER090W YKL211C + YER090W
4.1.3.27
TYROSINE PHENYLALANINE
D-ERYTHROSE-4- PHOSPHATE
GLYCERATE-2- PHOSPHATE
Anthranilate
C00065
C00001
C00463
Indole
TRYPTOPHAN
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--
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--
Model Revision
% Task E: Defeasible example
#example not predicted_growth(11, 1) =4.
H: -
C: 0 example/s out of 1
14-17/09/2014 ILP '14, Nancy 11
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--
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-- --
--
C00008
C00002
YDR127W
2.7.1.71
C00009
YDR127W
4.2.1.10
YDR127W
4.2.3.4
4.2.1.11 YGR254W YHR174W
YMR323W
C00074
C00065
C00118
C00078
C03506
C04302
YDR007W
5.3.1.24
YGL026C
4.2.1.20
C00119
C00013
C01302
C00011
YKL211C
4.1.1.48
YDR354W
2.4.2.18
C00944
C02637
C01269
C00009
C03175
C00009
YGL148W 4.2.3.5
YDR127W
2.5.1.19
C04691
C00009
YBR249C YDR035W
2.5.1.54
YDR127W
1.1.1.25
C00005 C00006
C00493
YBR166C 1.3.1.13
C00006
C00005
YNL316C 4.2.1.51
C00011 C00011
YPR060C 5.4.99.5
C00254
C01179
C00082
C00025
C00026
YHR137W YGL202W
2.6.1.1
C00025
C00079
YHR137W YGL202W
2.6.1.7
C00166
C00026
C00251
C00279 C00631
C00108
C00064 C00022 C00025
YER090W YKL211C + YER090W
4.1.3.27
TYROSINE PHENYLALANINE
D-ERYTHROSE-4- PHOSPHATE
GLYCERATE-2- PHOSPHATE
Anthranilate
C00065
C00001
C00463
Indole
TRYPTOPHAN
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Scalability Analysison Validation Experiments
14-17/09/2014 ILP '14, Nancy 12
stan
dar
dex
pre
ssio
ns
bia
sed
exp
ress
ion
s
# reactions time (s)hypotheses - means "out of memory"
Scalability Analysison data provided by Robot Scientist
14-17/09/2014 ILP '14, Nancy 13
30% faster!
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--
C00008
C00002
YDR127W
2.7.1.71
C00009
YDR127W
4.2.1.10
YDR127W
4.2.3.4
4.2.1.11 YGR254W YHR174W
YMR323W
C00074
C00065
C00118
C00078
C03506
C04302
YDR007W
5.3.1.24
YGL026C
4.2.1.20
C00119
C00013
C01302
C00011
YKL211C
4.1.1.48
YDR354W
2.4.2.18
C00944
C02637
C01269
C00009
C03175
C00009
YGL148W 4.2.3.5
YDR127W
2.5.1.19
C04691
C00009
YBR249C YDR035W
2.5.1.54
YDR127W
1.1.1.25
C00005 C00006
C00493
YBR166C 1.3.1.13
C00006
C00005
YNL316C 4.2.1.51
C00011 C00011
YPR060C 5.4.99.5
C00254
C01179
C00082
C00025
C00026
YHR137W YGL202W
2.6.1.1
C00025
C00079
YHR137W YGL202W
2.6.1.7
C00166
C00026
C00251
C00279 C00631
C00108
C00064 C00022 C00025
YER090W YKL211C + YER090W
4.1.3.27
TYROSINE PHENYLALANINE
D-ERYTHROSE-4- PHOSPHATE
GLYCERATE-2- PHOSPHATE
Anthranilate
C00065
C00001
C00463
Indole
TRYPTOPHAN
376
375
374
662
661
660
823
370
363
362
361
360
359
369
366 368
367 365, 357
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C00011
C00004
C00003
364
U52_ 1.3.1.12
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NONMONOTONIC LEARNING IN LARGE BIOLOGICAL NETWORKS
Stefano Bragaglia, Oliver [email protected], [email protected]
• Thanks for your attention
• Any questions?
14-17/09/2014 ILP '14, Nancy 14