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N Chemmangattuvalappil, K Task and I Banerjee
Abstract
Reverse engineering gene networks and identifying regulatory interactions are integral to understanding cellular decision making processes. Advancement in high throughput experimental techniques has initiated innovative data driven analysis of gene regulatory networks. However, inherent noise associated with biological systems requires numerous experimental replicates for reliable conclusions. Furthermore, evidence of robust algorithms directly exploiting basic biological traits are few. Such algorithms are expected to be efficient in their performance and robust in their prediction.
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Concepts
Discrete mathematics, Feedback, Algorithmic efficiency, Algorithm, Engineering, Systems biology, Decision making, Gene regulatory network
MeSH headings
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