doctoral consortium@ruleml2015: grools: reactive graph reasoning for genome annotation
TRANSCRIPT
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GROOLS
Reactive Graph Reasoning forGenome Annotation
Jonathan MERCIER
CEA - LABGeM France
August 4, 2015 / RuleML 2015, Berlin
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BiologyAsserted bio-fact from bio experiment
source code: https://github.com/Grools GROOLS 2 / 13
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BiologyGenome sequencing and annotation
source code: https://github.com/Grools GROOLS 3 / 13
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BiologyGenome sequencing and annotation
source code: https://github.com/Grools GROOLS 3 / 13
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BiologyGenome sequencing and annotation
source code: https://github.com/Grools GROOLS 3 / 13
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BiologyGenome sequencing and annotation
source code: https://github.com/Grools GROOLS 3 / 13
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BiologyGenome sequencing and annotation
source code: https://github.com/Grools GROOLS 3 / 13
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BiologyPredicted bio-fact by bio-annotator
source code: https://github.com/Grools GROOLS 4 / 13
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BiologyPredicted bio-fact by bio-annotator
source code: https://github.com/Grools GROOLS 4 / 13
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BiologyPredicted bio-fact by bio-annotator
source code: https://github.com/Grools GROOLS 4 / 13
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BiologyPredicted bio-fact by bio-annotator
source code: https://github.com/Grools GROOLS 4 / 13
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BiologyPredicted bio-fact by bio-annotator
source code: https://github.com/Grools GROOLS 4 / 13
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BiologyPredicted bio-fact by bio-annotator
source code: https://github.com/Grools GROOLS 4 / 13
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BiologyPredicted bio-fact by bio-annotator
source code: https://github.com/Grools GROOLS 4 / 13
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BiologyPredicted bio-fact by bio-annotator
source code: https://github.com/Grools GROOLS 4 / 13
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BiologyPredicted bio-fact by bio-annotator
source code: https://github.com/Grools GROOLS 4 / 13
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BiologyPredicted bio-fact by bio-annotator
source code: https://github.com/Grools GROOLS 4 / 13
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BioinformaticsGROOLS Object model
source code: https://github.com/Grools GROOLS 5 / 13
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BioinformaticsPrior knowledge DAG
source code: https://github.com/Grools GROOLS 6 / 13
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BioinformaticsPrior knowledge DAG
source code: https://github.com/Grools GROOLS 6 / 13
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BioinformaticsPrior knowledge DAG
source code: https://github.com/Grools GROOLS 6 / 13
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BioinformaticsPrior knowledge DAG
source code: https://github.com/Grools GROOLS 6 / 13
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BioinformaticsPrior knowledge DAG
source code: https://github.com/Grools GROOLS 6 / 13
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BioinformaticsPrior knowledge DAG
source code: https://github.com/Grools GROOLS 6 / 13
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BioinformaticsPrior knowledge DAG
source code: https://github.com/Grools GROOLS 6 / 13
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BioinformaticsPrior knowledge DAG
source code: https://github.com/Grools GROOLS 6 / 13
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BioinformaticsPrior knowledge DAG
source code: https://github.com/Grools GROOLS 6 / 13
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BioinformaticsPrior knowledge DAG
source code: https://github.com/Grools GROOLS 6 / 13
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BioinformaticsPrior knowledge DAG
source code: https://github.com/Grools GROOLS 6 / 13
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BioinformaticsPrior knowledge DAG
source code: https://github.com/Grools GROOLS 6 / 13
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Belnap’s logicTruth tables
Table: Four-valued logic truth tables. T: true, F: false, B: both, N: none.
F (¬α)T F
B B
N N
F T
F (∧α) T B N F
T T B N F
B B B F F
N N F N F
F F F F F
F (∨α) T B N F
T T T T T
B T B T B
N T T N N
F T B N F
source code: https://github.com/Grools GROOLS 7 / 13
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BioinformaticsObject-Oriented Expert System
source code: https://github.com/Grools GROOLS 8 / 13
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BioinformaticsDAG Reasoning
source code: https://github.com/Grools GROOLS 9 / 13
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BioinformaticsDAG Reasoning
source code: https://github.com/Grools GROOLS 9 / 13
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BioinformaticsDAG Reasoning
source code: https://github.com/Grools GROOLS 10 / 13
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BioinformaticsDAG Reasoning
source code: https://github.com/Grools GROOLS 10 / 13
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Conclusion truth table
Table: Sixteen-valued logic truth tablehhhhhhhhhAssertion
PredictionPRESENT ABSENT BOTH UNKNOWN
REQUIRED Confirmed P. Unexpected A. Contradictory A. MissingAVOIDED Unexpected P. Confirmed A. Contradictory P. AbsentBOTH Ambiguous P. Ambiguous A. Ambiguous C. AmbiguousUNKNOWN Unconfirmed P. Unconfirmed A. Unconfirmed C. Unknown
LegendA. AbsenceP. PresenceC. Contradiction
source code: https://github.com/Grools GROOLS 11 / 13
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Perspective
▶ Applying to real data
▶ Data mining
source code: https://github.com/Grools GROOLS 12 / 13
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Perspective
▶ Applying to real data
▶ Data mining
source code: https://github.com/Grools GROOLS 12 / 13
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Acknowledgements
LABGeM systems biology team:David VallenetClaudine MedigueKarine BastardMark Stam
Special thanks to:Alain Viari (INRIA)Anne Morgat (SIB)UniProt team (EBI-SIB)
source code: https://github.com/Grools GROOLS 13 / 13