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                <term xml:lang="en">Gene knockout prediction</term>
                <term xml:lang="en">Synthetic biology</term>
                <term xml:lang="en">Systems biology</term>
                <term xml:lang="en">Metabolism</term>
                <term xml:lang="en">Reaction networks</term>
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              <p>Algorithms based on abstract interpretation were proposed recently for predicting changes of reaction networks with partial kinetic information. Their prediction precision, however, depends heavily on which heuristics are applied in order to add linear consequences of the steady state equations of the metabolic network. In this paper we ask the question whether such heuristics can be avoided while obtaining the highest possible precision. This leads us to the first algorithm for computing the difference abstractions of a linear equation system exactly without any approximation. This algorithm relies on the usage of elementary flux modes in a nontrivial manner, first-order definitions of the abstractions, and finite domain constraint solving.A journal version at TCS'2021 is available at: &lt;a href="https://hal.inria.fr/hal-03156136"&gt;https://hal.inria.fr/hal-03156136&lt;/a&gt;</p>
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