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Discovery of Boolean metabolic networks:integer linear programming based approach

机译:Boolean代谢网络的发现:基于整数的线性编程方法

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Background: Traditional drug discovery methods focused on the efficacy of drugs rather than their toxicity. However, toxicity and/or lack of efficacy are produced when unintended targets are affected in metabolic networks. Thus, identification of biological targets which can be manipulated to produce the desired effect with minimum side-effects has become an important and challenging topic. Efficient computational methods are required to identify the drug targets while incurring minimal side-effects.
机译:背景:传统的药物发现方法专注于毒品的疗效而不是毒性。然而,当意外目标在代谢网络中受到影响时,产生毒性和/或缺乏功效。因此,可以操纵生物靶标以产生与最小副作用产生所需效果的生物靶标成为一个重要和具有挑战性的话题。需要有效的计算方法来识别药物靶标,同时产生最小的副作用。

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