Integration of abduction and induction in biological networks using CF-induction Yoshitaka Yamamoto Graduate University for Advanced Studies Tokyo, Japan. Andrei Doncescu LAAS-CNRS Toulouse, France. Katsumi Inoue National Institute of Informatics Tokyo, Japan. FJ’07
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Integration of abduction and induction in biological networks using CF-induction Yoshitaka Yamamoto Graduate University for Advanced Studies Tokyo, Japan.
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Integration of abduction and induction in biological networks
using CF-induction
Yoshitaka YamamotoGraduate University for Advanced Studies Tokyo, Japan.
Andrei DoncescuLAAS-CNRS Toulouse, France.
Katsumi InoueNational Institute of Informatics Tokyo, Japan.
FJ’07
Our goal• Modeling of biological systems:
– Explain and predict the metabolic pathway into the cell
• CF-induction CF-induction (Inoue 2004: Yamamoto, Ray & Inoue 2007)
• fc-HAILfc-HAIL (Inoue & Ray 2007)B, E, H: full clausal theory
• Note: CF-induction is the only existing ILP system that is complete for full clausal theories.
B ∧ ¬ E ⊨ ¬ H (IE) ⇔ B ∧ ¬ E ⊨ Carc(B ∧ ¬ E, P) ⊨ ¬ H . CC ⊨ ¬ H where CC ⊆ Instances(Carc(B ∧ ¬ E, P)) .
H ⊨ F where F is ¬ CC in CNF .
Principle of CF-induction
Algorithm1.Compute Carc(B ∧ ¬ E , P) .
2.Construct a bridge formula CC .
3.Convert ¬ CC into CNF F .
4.Generalize F to H such that
B ∧ H is consistent;
H is Skolem-free.
* Generalization
H ⊨ F - inverse Skolemization- anti-instantiation- dropping literals from clauses - addition of clauses - inverse resolution - Plotkin’s least generalization
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Outline
Logical Setting of Abduction and Induction
CF-induction (CFI) Consequence finding
Procedure of CF-induction
Features of CF-induction
Inhibition in metabolic networks Simplification of metabolic networks
How enzymes work
Effect on toxins
Prediction for inhibition in metabolic networks
Integration abduction and induction on the inhibitory effect using CFI
Goals-Predicting the concentration of metabolites intracellular
-Discovering inductive rules augmenting incomplete background theory
Our Approaches- Using CF-induction
Prediction for intracellular fluxes
Examples E :
changes (up or down) of concentrations of metabolites extracelluar
• Background theory B : - chemical reactions in a metabolic networks - two clauses concerning the inhibitory effect
Hypothesis H : - a clausal theory which consists of both lierals whose predicate is “inhibition” and clauses corresponding to inductive rules
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Metabolite Balancing
• Intracellular fluxes are determined as a function of the measurable extracellular fluxes using a stoichiometric model for major intracellular reactions and applying a mass balance around each intracellular metabolite.
v1, v2, v3+, v3-, v4 : unknown fluxes at the steady state. rA, rC, rD, rE : metabolite extracellular accumulation rate.
A
E
DB
C
rA
rC
rE
rD
v3+v5
v4v3-
v2v1
( ) ( )[ ]⎪⎪⎪⎪
⎩
⎪⎪⎪⎪
⎨
⎧
−−+=−+=−−=
−=−=
−=
3v3vá
árCrE5v
árD1v5v
árC4v
á1v2v
rA1v
E : concentration(d, up). concentration(e, down). concentration(c, down).