Ontology-Based Classification of Molecules: a Logic Programming Approach
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The document discusses an ontology-based classification of molecules using logic programming, focusing on the benefits of semantic technologies for fast, automatic classification of biochemical knowledge. It highlights the limitations of the Web Ontology Language (OWL) in representing complex molecular structures, especially regarding cyclical representations. The work demonstrates a formalism and implementation capable of efficiently classifying structured chemical objects using a structure-based approach, while revealing modeling errors in existing ontologies.
![E MPIRICAL E VALUATION
Draws upon DLV, a deductive databases engine
Evaluation with data extracted from ChEBI
500 molecules under 51 chemical classes in 40 secs
Quicker than other approaches:
[Hastings et al., 2010] 140 molecules in 4 hours
[Magka et al., 2012] 70 molecules in 450 secs
7](https://image.slidesharecdn.com/swat4lsslides-magka-121202063149-phpapp02/85/Ontology-Based-Classification-of-Molecules-a-Logic-Programming-Approach-60-320.jpg)
![E MPIRICAL E VALUATION
Draws upon DLV, a deductive databases engine
Evaluation with data extracted from ChEBI
500 molecules under 51 chemical classes in 40 secs
Quicker than other approaches:
[Hastings et al., 2010] 140 molecules in 4 hours
[Magka et al., 2012] 70 molecules in 450 secs
Subsumptions exposed by our prototype:
7](https://image.slidesharecdn.com/swat4lsslides-magka-121202063149-phpapp02/85/Ontology-Based-Classification-of-Molecules-a-Logic-Programming-Approach-61-320.jpg)
![E MPIRICAL E VALUATION
Draws upon DLV, a deductive databases engine
Evaluation with data extracted from ChEBI
500 molecules under 51 chemical classes in 40 secs
Quicker than other approaches:
[Hastings et al., 2010] 140 molecules in 4 hours
[Magka et al., 2012] 70 molecules in 450 secs
Subsumptions exposed by our prototype:
ascorbic acid is a polyatomic entity, a carboxylic ester and a
cyclic molecule
missing from the ChEBI OWL ontology
7](https://image.slidesharecdn.com/swat4lsslides-magka-121202063149-phpapp02/85/Ontology-Based-Classification-of-Molecules-a-Logic-Programming-Approach-62-320.jpg)
![E MPIRICAL E VALUATION
Draws upon DLV, a deductive databases engine
Evaluation with data extracted from ChEBI
500 molecules under 51 chemical classes in 40 secs
Quicker than other approaches:
[Hastings et al., 2010] 140 molecules in 4 hours
[Magka et al., 2012] 70 molecules in 450 secs
Subsumptions exposed by our prototype:
ascorbic acid is a polyatomic entity, a carboxylic ester and a
cyclic molecule
missing from the ChEBI OWL ontology
Contradictory subclass relation from ChEBI:
7](https://image.slidesharecdn.com/swat4lsslides-magka-121202063149-phpapp02/85/Ontology-Based-Classification-of-Molecules-a-Logic-Programming-Approach-63-320.jpg)
![E MPIRICAL E VALUATION
Draws upon DLV, a deductive databases engine
Evaluation with data extracted from ChEBI
500 molecules under 51 chemical classes in 40 secs
Quicker than other approaches:
[Hastings et al., 2010] 140 molecules in 4 hours
[Magka et al., 2012] 70 molecules in 450 secs
Subsumptions exposed by our prototype:
ascorbic acid is a polyatomic entity, a carboxylic ester and a
cyclic molecule
missing from the ChEBI OWL ontology
Contradictory subclass relation from ChEBI:
Ascorbic acid is asserted to be a carboxylic acid (release 95)
Not listed among the subsumptions derived by our prototype
7](https://image.slidesharecdn.com/swat4lsslides-magka-121202063149-phpapp02/85/Ontology-Based-Classification-of-Molecules-a-Logic-Programming-Approach-64-320.jpg)
![C ONCLUSION AND F URTHER R ESEARCH
Results
1 Expressive and decidable formalism for complex objects
2 Wide range of structure-based classes
3 DLV-based implementation exhibits a significant speedup
4 Evaluation over ChEBI ontology revealed modelling errors
Language for representing biochemical structures with a
favourable performance/expressivity trade-off
Future directions
SMILES-based surface syntax
define carboxylicEster
some hasAtom SMILES(COC(= O)[∗])
end.
8](https://image.slidesharecdn.com/swat4lsslides-magka-121202063149-phpapp02/85/Ontology-Based-Classification-of-Molecules-a-Logic-Programming-Approach-72-320.jpg)
Ontology-Based Classification of Molecules: a Logic Programming Approach
- 1. O NTOLOGY-BASED C LASSIFICATION OF M OLECULES : A L OGIC P ROGRAMMING A PPROACH Despoina Magka Department of Computer Science, University of Oxford November 30, 2012
- 2. B IOINFORMATICS AND S EMANTIC T ECHNOLOGIES Life sciences data deluge 1
- 3. B IOINFORMATICS AND S EMANTIC T ECHNOLOGIES Life sciences data deluge Hierarchical organisation of biochemical knowledge 1
- 4. B IOINFORMATICS AND S EMANTIC T ECHNOLOGIES Life sciences data deluge Hierarchical organisation of biochemical knowledge 1
- 5. B IOINFORMATICS AND S EMANTIC T ECHNOLOGIES Life sciences data deluge Hierarchical organisation of biochemical knowledge 1
- 6. B IOINFORMATICS AND S EMANTIC T ECHNOLOGIES Life sciences data deluge Hierarchical organisation of biochemical knowledge Fast, automatic and repeatable classification driven by Semantic technologies 1
- 7. B IOINFORMATICS AND S EMANTIC T ECHNOLOGIES Life sciences data deluge Hierarchical organisation of biochemical knowledge Fast, automatic and repeatable classification driven by Semantic technologies Web Ontology Language, a W3C standard family of logic-based formalisms 1
- 8. B IOINFORMATICS AND S EMANTIC T ECHNOLOGIES Life sciences data deluge Hierarchical organisation of biochemical knowledge Fast, automatic and repeatable classification driven by Semantic technologies Web Ontology Language, a W3C standard family of logic-based formalisms OWL bio- and chemo-ontologies widely adopted 1
- 9. T HE C H EBI O NTOLOGY OWL ontology Chemical Entities of Biological Interest 2
- 10. T HE C H EBI O NTOLOGY OWL ontology Chemical Entities of Biological Interest Dictionary of molecules with taxonomical information 2
- 11. T HE C H EBI O NTOLOGY OWL ontology Chemical Entities of Biological Interest Dictionary of molecules with taxonomical information caffeine is a cyclic molecule 2
- 12. T HE C H EBI O NTOLOGY OWL ontology Chemical Entities of Biological Interest Dictionary of molecules with taxonomical information serotonin is an organic molecule 2
- 13. T HE C H EBI O NTOLOGY OWL ontology Chemical Entities of Biological Interest Dictionary of molecules with taxonomical information ascorbic acid is a carboxylic ester 2
- 14. T HE C H EBI O NTOLOGY OWL ontology Chemical Entities of Biological Interest Dictionary of molecules with taxonomical information Pharmaceutical design and study of biological pathways 2
- 15. T HE C H EBI O NTOLOGY OWL ontology Chemical Entities of Biological Interest Dictionary of molecules with taxonomical information Pharmaceutical design and study of biological pathways ChEBI is manually incremented 2
- 16. T HE C H EBI O NTOLOGY OWL ontology Chemical Entities of Biological Interest Dictionary of molecules with taxonomical information Pharmaceutical design and study of biological pathways ChEBI is manually incremented Currently ~30,000 chemical entities, expands at 3,500/yr 2
- 17. T HE C H EBI O NTOLOGY OWL ontology Chemical Entities of Biological Interest Dictionary of molecules with taxonomical information Pharmaceutical design and study of biological pathways ChEBI is manually incremented Currently ~30,000 chemical entities, expands at 3,500/yr Existing chemical databases describe millions of molecules 2
- 18. T HE C H EBI O NTOLOGY OWL ontology Chemical Entities of Biological Interest Dictionary of molecules with taxonomical information Pharmaceutical design and study of biological pathways ChEBI is manually incremented Currently ~30,000 chemical entities, expands at 3,500/yr Existing chemical databases describe millions of molecules Speed up growth by automating chemical classification 2
- 19. E XPRESSIVITY L IMITATIONS OF OWL 1 At least one tree-shaped model for each consistent OWL ontology problematic representation of cycles 3
- 20. E XPRESSIVITY L IMITATIONS OF OWL 1 At least one tree-shaped model for each consistent OWL ontology problematic representation of cycles E XAMPLE C C C C 3
- 21. E XPRESSIVITY L IMITATIONS OF OWL 1 At least one tree-shaped model for each consistent OWL ontology problematic representation of cycles E XAMPLE Cyclobutane ∃(= 4)hasAtom.(Carbon ∃(= 2)hasBond.Carbon) C C C C 3
- 22. E XPRESSIVITY L IMITATIONS OF OWL 1 At least one tree-shaped model for each consistent OWL ontology problematic representation of cycles E XAMPLE Cyclobutane ∃(= 4)hasAtom.(Carbon ∃(= 2)hasBond.Carbon) C C C C 3
- 23. E XPRESSIVITY L IMITATIONS OF OWL 1 At least one tree-shaped model for each consistent OWL ontology problematic representation of cycles E XAMPLE Cyclobutane ∃(= 4)hasAtom.(Carbon ∃(= 2)hasBond.Carbon) C C C C OWL-based reasoning support 1 Is cyclobutane a cyclic molecule? 3
- 24. E XPRESSIVITY L IMITATIONS OF OWL 1 At least one tree-shaped model for each consistent OWL ontology problematic representation of cycles 2 No minimality condition on the models hard to axiomatise classes based on the absence of attributes E XAMPLE Cyclobutane ∃(= 4)hasAtom.(Carbon ∃(= 2)hasBond.Carbon) C C C C OWL-based reasoning support 1 Is cyclobutane a cyclic molecule? 3
- 25. E XPRESSIVITY L IMITATIONS OF OWL 1 At least one tree-shaped model for each consistent OWL ontology problematic representation of cycles 2 No minimality condition on the models hard to axiomatise classes based on the absence of attributes E XAMPLE Cyclobutane ∃(= 4)hasAtom.(Carbon ∃(= 2)hasBond.Carbon) Oxygen C C C C OWL-based reasoning support 1 Is cyclobutane a cyclic molecule? 3
- 26. E XPRESSIVITY L IMITATIONS OF OWL 1 At least one tree-shaped model for each consistent OWL ontology problematic representation of cycles 2 No minimality condition on the models hard to axiomatise classes based on the absence of attributes E XAMPLE Cyclobutane ∃(= 4)hasAtom.(Carbon ∃(= 2)hasBond.Carbon) Oxygen C C C C OWL-based reasoning support 1 Is cyclobutane a cyclic molecule? 2 Is cyclobutane a hydrocarbon? 3
- 27. E XPRESSIVITY L IMITATIONS OF OWL 1 At least one tree-shaped model for each consistent OWL ontology problematic representation of cycles 2 No minimality condition on the models hard to axiomatise classes based on the absence of attributes E XAMPLE Cyclobutane ∃(= 4)hasAtom.(Carbon ∃(= 2)hasBond.Carbon) Oxygen C C C C 3
- 28. E XPRESSIVITY L IMITATIONS OF OWL 1 At least one tree-shaped model for each consistent OWL ontology problematic representation of cycles 2 No minimality condition on the models hard to axiomatise classes based on the absence of attributes E XAMPLE Cyclobutane ∃(= 4)hasAtom.(Carbon ∃(= 2)hasBond.Carbon) Oxygen C C C C Required reasoning support 1 Is cyclobutane a cyclic molecule? 2 Is cyclobutane a hydrocarbon? 3
- 29. E XPRESSIVITY L IMITATIONS OF OWL 1 At least one tree-shaped model for each consistent OWL ontology problematic representation of cycles 2 No minimality condition on the models hard to axiomatise classes based on the absence of attributes E XAMPLE Cyclobutane ∃(= 4)hasAtom.(Carbon ∃(= 2)hasBond.Carbon) Oxygen C C C C Required reasoning support 1 Is cyclobutane a cyclic molecule? 2 Is cyclobutane a hydrocarbon? 3
- 30. R ESULTS OVERVIEW 1 Expressive and decidable formalism for modelling complex objects: Description Graphs Logic Programs 4
- 31. R ESULTS OVERVIEW 1 Expressive and decidable formalism for modelling complex objects: Description Graphs Logic Programs 2 Modelling that spans a wide range of structure-dependent classes of molecules 4
- 32. R ESULTS OVERVIEW 1 Expressive and decidable formalism for modelling complex objects: Description Graphs Logic Programs 2 Modelling that spans a wide range of structure-dependent classes of molecules 3 Implementation that draws upon DLV and performs structure-based classification with a significant speedup 4
- 33. R ESULTS OVERVIEW 1 Expressive and decidable formalism for modelling complex objects: Description Graphs Logic Programs 2 Modelling that spans a wide range of structure-dependent classes of molecules 3 Implementation that draws upon DLV and performs structure-based classification with a significant speedup 4 Evaluation over part of the manually curated ChEBI ontology revealed modelling errors 4
- 34. R ESULTS OVERVIEW 1 Expressive and decidable formalism for modelling complex objects: Description Graphs Logic Programs 2 Modelling that spans a wide range of structure-dependent classes of molecules 3 Implementation that draws upon DLV and performs structure-based classification with a significant speedup 4 Evaluation over part of the manually curated ChEBI ontology revealed modelling errors Language for representing biochemical structures with a favourable performance/expressivity trade-off 4
- 35. C LASSIFYING S TRUCTURED O BJECTS 5
- 36. C LASSIFYING S TRUCTURED O BJECTS ascorbicAcid : 0 o 6 o c o o 5 c 11 c 1 c hasAtom h 2 12 10 7 single c c 13 double 9 8 4 o 3 o 5
- 37. C LASSIFYING S TRUCTURED O BJECTS ascorbicAcid : 0 o 6 o c o o 5 c 11 c 1 c hasAtom h 2 12 10 7 single c c 13 double 9 8 4 o 3 o ascorbicAcid(x) →hasAtom(x, f1 (x)) ∧ . . . ∧ hasAtom(x, f13 (x)) o(f1 (x)) ∧ . . . ∧ c(f7 (x)) ∧ . . . ∧ single(f1 (x), f7 (x)) ∧ double(f7 (x), f2 (x)) ∧ . . . 5
- 38. C LASSIFYING S TRUCTURED O BJECTS ascorbicAcid : 0 o 6 o c o o 5 c 11 c 1 c hasAtom h 2 12 10 7 single c c 13 double 9 8 4 o 3 o ascorbicAcid(x) →hasAtom(x, f1 (x)) ∧ . . . ∧ hasAtom(x, f13 (x)) o(f1 (x)) ∧ . . . ∧ c(f7 (x)) ∧ . . . ∧ single(f1 (x), f7 (x)) ∧ double(f7 (x), f2 (x)) ∧ . . . hasAtom(x, y1 ) ∧ hasAtom(x, y2 ) ∧ y1 = y2 → polyatomicEntity(x) ∧5 hasAtom(x, yi ) ∧ c(y1 ) ∧ o(y2 ) ∧ o(y3 )∧ i=1 c(y4 ) ∧ horc(y5 ) ∧ double(y1 , y2 )∧ single(y1 , y3 ) ∧ single(y3 , y4 ) ∧ single(y1 , y5 ) → carboxylicEster(x) 5
- 39. C LASSIFYING S TRUCTURED O BJECTS ascorbicAcid : 0 o 6 o c o o 5 c 11 c 1 c hasAtom h 2 12 10 7 single c c 13 double 9 8 4 o 3 o Input fact: ascorbicAcid(a) Stable model: ascorbicAcid(a), hasAtom(a, af ) for 1 ≤ i ≤ 13, i o(af ) for 1 ≤ i ≤ 6, c(af ) for 7 ≤ i ≤ 12, h(af ), single(af , af ), i i 13 8 3 single(af , af ), single(af , af ) for i ∈ {5, 11}, single(af , af ), 9 4 12 i 11 6 single(af , af ) for i ∈ {1, 9, 11, 13}, single(af , af ) for i ∈ {1, 8}, 10 i 7 i double(af , af ), double(af , af ), horc(af ) for 7 ≤ i ≤ 13, 2 7 8 9 i polyatomicEntity(a), carboxylicEster(a), cyclic(a) 5
- 40. C LASSIFYING S TRUCTURED O BJECTS ascorbicAcid : 0 o 6 o c o o 5 c 11 c 1 c hasAtom h 2 12 10 7 single c c 13 double 9 8 4 o 3 o Input fact: ascorbicAcid(a) Stable model: ascorbicAcid(a), hasAtom(a, af ) for 1 ≤ i ≤ 13, i o(af ) for 1 ≤ i ≤ 6, c(af ) for 7 ≤ i ≤ 12, h(af ), single(af , af ), i i 13 8 3 single(af , af ), single(af , af ) for i ∈ {5, 11}, single(af , af ), 9 4 12 i 11 6 single(af , af ) for i ∈ {1, 9, 11, 13}, single(af , af ) for i ∈ {1, 8}, 10 i 7 i double(af , af ), double(af , af ), horc(af ) for 7 ≤ i ≤ 13, 2 7 8 9 i polyatomicEntity(a), carboxylicEster(a), cyclic(a) Ascorbic acid is a cyclic polyatomic entity and a carboxylic ester 5
- 41. C HEMICAL C LASSES W E C OVERED 1 Existence of subcomponents 6
- 42. C HEMICAL C LASSES W E C OVERED 1 Existence of subcomponents Carbon molecules 6
- 43. C HEMICAL C LASSES W E C OVERED 1 Existence of subcomponents Carbon molecules Carboxylic acids and carboxylic esters 6
- 44. C HEMICAL C LASSES W E C OVERED 1 Existence of subcomponents Carbon molecules Carboxylic acids and carboxylic esters Ketones and aldehydes 6
- 45. C HEMICAL C LASSES W E C OVERED 1 Existence of subcomponents Carbon molecules Carboxylic acids and carboxylic esters Ketones and aldehydes 2 Exact cardinality of parts 6
- 46. C HEMICAL C LASSES W E C OVERED 1 Existence of subcomponents Carbon molecules Carboxylic acids and carboxylic esters Ketones and aldehydes 2 Exact cardinality of parts Exactly two carbons 6
- 47. C HEMICAL C LASSES W E C OVERED 1 Existence of subcomponents Carbon molecules Carboxylic acids and carboxylic esters Ketones and aldehydes 2 Exact cardinality of parts Exactly two carbons Dicarboxylic acid 6
- 48. C HEMICAL C LASSES W E C OVERED 1 Existence of subcomponents Carbon molecules Carboxylic acids and carboxylic esters Ketones and aldehydes 2 Exact cardinality of parts Exactly two carbons Dicarboxylic acid 3 Exclusive composition 6
- 49. C HEMICAL C LASSES W E C OVERED 1 Existence of subcomponents Carbon molecules Carboxylic acids and carboxylic esters Ketones and aldehydes 2 Exact cardinality of parts Exactly two carbons Dicarboxylic acid 3 Exclusive composition Inorganic molecules 6
- 50. C HEMICAL C LASSES W E C OVERED 1 Existence of subcomponents Carbon molecules Carboxylic acids and carboxylic esters Ketones and aldehydes 2 Exact cardinality of parts Exactly two carbons Dicarboxylic acid 3 Exclusive composition Inorganic molecules Hydrocarbons 6
- 51. C HEMICAL C LASSES W E C OVERED 1 Existence of subcomponents Carbon molecules Carboxylic acids and carboxylic esters Ketones and aldehydes 2 Exact cardinality of parts Exactly two carbons Dicarboxylic acid 3 Exclusive composition Inorganic molecules Hydrocarbons Saturated molecules 6
- 52. C HEMICAL C LASSES W E C OVERED 1 Existence of subcomponents Carbon molecules Carboxylic acids and carboxylic esters Ketones and aldehydes 2 Exact cardinality of parts Exactly two carbons Dicarboxylic acid 3 Exclusive composition Inorganic molecules Hydrocarbons Saturated molecules 4 Cyclicity-related classes 6
- 53. C HEMICAL C LASSES W E C OVERED 1 Existence of subcomponents Carbon molecules Carboxylic acids and carboxylic esters Ketones and aldehydes 2 Exact cardinality of parts Exactly two carbons Dicarboxylic acid 3 Exclusive composition Inorganic molecules Hydrocarbons Saturated molecules 4 Cyclicity-related classes Benzenes 6
- 54. C HEMICAL C LASSES W E C OVERED 1 Existence of subcomponents Carbon molecules Carboxylic acids and carboxylic esters Ketones and aldehydes 2 Exact cardinality of parts Exactly two carbons Dicarboxylic acid 3 Exclusive composition Inorganic molecules Hydrocarbons Saturated molecules 4 Cyclicity-related classes Benzenes Cyclic molecules 6
- 55. C HEMICAL C LASSES W E C OVERED 1 Existence of subcomponents Carbon molecules Carboxylic acids and carboxylic esters Ketones and aldehydes 2 Exact cardinality of parts Exactly two carbons Dicarboxylic acid 3 Exclusive composition Inorganic molecules Hydrocarbons Saturated molecules 4 Cyclicity-related classes Benzenes Cyclic molecules Alkanes 6
- 56. E MPIRICAL E VALUATION Draws upon DLV, a deductive databases engine 7
- 57. E MPIRICAL E VALUATION Draws upon DLV, a deductive databases engine Evaluation with data extracted from ChEBI 7
- 58. E MPIRICAL E VALUATION Draws upon DLV, a deductive databases engine Evaluation with data extracted from ChEBI 500 molecules under 51 chemical classes in 40 secs 7
- 59. E MPIRICAL E VALUATION Draws upon DLV, a deductive databases engine Evaluation with data extracted from ChEBI 500 molecules under 51 chemical classes in 40 secs Quicker than other approaches: 7
- 60. E MPIRICAL E VALUATION Draws upon DLV, a deductive databases engine Evaluation with data extracted from ChEBI 500 molecules under 51 chemical classes in 40 secs Quicker than other approaches: [Hastings et al., 2010] 140 molecules in 4 hours [Magka et al., 2012] 70 molecules in 450 secs 7
- 61. E MPIRICAL E VALUATION Draws upon DLV, a deductive databases engine Evaluation with data extracted from ChEBI 500 molecules under 51 chemical classes in 40 secs Quicker than other approaches: [Hastings et al., 2010] 140 molecules in 4 hours [Magka et al., 2012] 70 molecules in 450 secs Subsumptions exposed by our prototype: 7
- 62. E MPIRICAL E VALUATION Draws upon DLV, a deductive databases engine Evaluation with data extracted from ChEBI 500 molecules under 51 chemical classes in 40 secs Quicker than other approaches: [Hastings et al., 2010] 140 molecules in 4 hours [Magka et al., 2012] 70 molecules in 450 secs Subsumptions exposed by our prototype: ascorbic acid is a polyatomic entity, a carboxylic ester and a cyclic molecule missing from the ChEBI OWL ontology 7
- 63. E MPIRICAL E VALUATION Draws upon DLV, a deductive databases engine Evaluation with data extracted from ChEBI 500 molecules under 51 chemical classes in 40 secs Quicker than other approaches: [Hastings et al., 2010] 140 molecules in 4 hours [Magka et al., 2012] 70 molecules in 450 secs Subsumptions exposed by our prototype: ascorbic acid is a polyatomic entity, a carboxylic ester and a cyclic molecule missing from the ChEBI OWL ontology Contradictory subclass relation from ChEBI: 7
- 64. E MPIRICAL E VALUATION Draws upon DLV, a deductive databases engine Evaluation with data extracted from ChEBI 500 molecules under 51 chemical classes in 40 secs Quicker than other approaches: [Hastings et al., 2010] 140 molecules in 4 hours [Magka et al., 2012] 70 molecules in 450 secs Subsumptions exposed by our prototype: ascorbic acid is a polyatomic entity, a carboxylic ester and a cyclic molecule missing from the ChEBI OWL ontology Contradictory subclass relation from ChEBI: Ascorbic acid is asserted to be a carboxylic acid (release 95) Not listed among the subsumptions derived by our prototype 7
- 65. C ONCLUSION AND F URTHER R ESEARCH Results 1 Expressive and decidable formalism for complex objects 8
- 66. C ONCLUSION AND F URTHER R ESEARCH Results 1 Expressive and decidable formalism for complex objects 2 Wide range of structure-based classes 8
- 67. C ONCLUSION AND F URTHER R ESEARCH Results 1 Expressive and decidable formalism for complex objects 2 Wide range of structure-based classes 3 DLV-based implementation exhibits a significant speedup 8
- 68. C ONCLUSION AND F URTHER R ESEARCH Results 1 Expressive and decidable formalism for complex objects 2 Wide range of structure-based classes 3 DLV-based implementation exhibits a significant speedup 4 Evaluation over ChEBI ontology revealed modelling errors 8
- 69. C ONCLUSION AND F URTHER R ESEARCH Results 1 Expressive and decidable formalism for complex objects 2 Wide range of structure-based classes 3 DLV-based implementation exhibits a significant speedup 4 Evaluation over ChEBI ontology revealed modelling errors Language for representing biochemical structures with a favourable performance/expressivity trade-off 8
- 70. C ONCLUSION AND F URTHER R ESEARCH Results 1 Expressive and decidable formalism for complex objects 2 Wide range of structure-based classes 3 DLV-based implementation exhibits a significant speedup 4 Evaluation over ChEBI ontology revealed modelling errors Language for representing biochemical structures with a favourable performance/expressivity trade-off Future directions SMILES-based surface syntax 8
- 71. C ONCLUSION AND F URTHER R ESEARCH Results 1 Expressive and decidable formalism for complex objects 2 Wide range of structure-based classes 3 DLV-based implementation exhibits a significant speedup 4 Evaluation over ChEBI ontology revealed modelling errors Language for representing biochemical structures with a favourable performance/expressivity trade-off Future directions SMILES-based surface syntax ∧5 hasAtom(x, yi ) ∧ c(y1 ) ∧ o(y2 ) ∧ o(y3 ) ∧ c(y4 )∧ i=1 double(y1 , y2 ) ∧ single(y1 , y3 ) ∧ single(y3 , y4 ) ∧ single(y1 , y5 ) → carboxylicEster(x) 8
- 72. C ONCLUSION AND F URTHER R ESEARCH Results 1 Expressive and decidable formalism for complex objects 2 Wide range of structure-based classes 3 DLV-based implementation exhibits a significant speedup 4 Evaluation over ChEBI ontology revealed modelling errors Language for representing biochemical structures with a favourable performance/expressivity trade-off Future directions SMILES-based surface syntax define carboxylicEster some hasAtom SMILES(COC(= O)[∗]) end. 8
- 73. C ONCLUSION AND F URTHER R ESEARCH Results 1 Expressive and decidable formalism for complex objects 2 Wide range of structure-based classes 3 DLV-based implementation exhibits a significant speedup 4 Evaluation over ChEBI ontology revealed modelling errors Language for representing biochemical structures with a favourable performance/expressivity trade-off Future directions SMILES-based surface syntax Detect subsumptions between classes 8
- 74. C ONCLUSION AND F URTHER R ESEARCH Results 1 Expressive and decidable formalism for complex objects 2 Wide range of structure-based classes 3 DLV-based implementation exhibits a significant speedup 4 Evaluation over ChEBI ontology revealed modelling errors Language for representing biochemical structures with a favourable performance/expressivity trade-off Future directions SMILES-based surface syntax Detect subsumptions between classes E.g., Carboxylic ester is an organic molecular entity 8
- 75. C ONCLUSION AND F URTHER R ESEARCH Results 1 Expressive and decidable formalism for complex objects 2 Wide range of structure-based classes 3 DLV-based implementation exhibits a significant speedup 4 Evaluation over ChEBI ontology revealed modelling errors Language for representing biochemical structures with a favourable performance/expressivity trade-off Future directions SMILES-based surface syntax Detect subsumptions between classes Extensions with numerical datatypes 8
- 76. C ONCLUSION AND F URTHER R ESEARCH Results 1 Expressive and decidable formalism for complex objects 2 Wide range of structure-based classes 3 DLV-based implementation exhibits a significant speedup 4 Evaluation over ChEBI ontology revealed modelling errors Language for representing biochemical structures with a favourable performance/expressivity trade-off Future directions SMILES-based surface syntax Detect subsumptions between classes Extensions with numerical datatypes E.g., Small molecules if they weigh less than 800 daltons 8
- 77. C ONCLUSION AND F URTHER R ESEARCH Results 1 Expressive and decidable formalism for complex objects 2 Wide range of structure-based classes 3 DLV-based implementation exhibits a significant speedup 4 Evaluation over ChEBI ontology revealed modelling errors Language for representing biochemical structures with a favourable performance/expressivity trade-off Future directions SMILES-based surface syntax Detect subsumptions between classes Extensions with numerical datatypes Classification of complex biological objects 8
- 78. C ONCLUSION AND F URTHER R ESEARCH Results 1 Expressive and decidable formalism for complex objects 2 Wide range of structure-based classes 3 DLV-based implementation exhibits a significant speedup 4 Evaluation over ChEBI ontology revealed modelling errors Language for representing biochemical structures with a favourable performance/expressivity trade-off Future directions SMILES-based surface syntax Detect subsumptions between classes Extensions with numerical datatypes Classification of complex biological objects Integration with Protégé, Bioclipse, JChemPaint,. . . 8
- 79. C ONCLUSION AND F URTHER R ESEARCH Results 1 Expressive and decidable formalism for complex objects 2 Wide range of structure-based classes 3 DLV-based implementation exhibits a significant speedup 4 Evaluation over ChEBI ontology revealed modelling errors Language for representing biochemical structures with a favourable performance/expressivity trade-off Future directions SMILES-based surface syntax Detect subsumptions between classes Extensions with numerical datatypes Classification of complex biological objects Integration with Protégé, Bioclipse, JChemPaint,. . . Mapping from our logic to RDF 8
- 80. C ONCLUSION AND F URTHER R ESEARCH Results 1 Expressive and decidable formalism for complex objects 2 Wide range of structure-based classes 3 DLV-based implementation exhibits a significant speedup 4 Evaluation over ChEBI ontology revealed modelling errors Language for representing biochemical structures with a favourable performance/expressivity trade-off Future directions SMILES-based surface syntax Detect subsumptions between classes Extensions with numerical datatypes Classification of complex biological objects Integration with Protégé, Bioclipse, JChemPaint,. . . Mapping from our logic to RDF Thank you! Questions?!? 8