{"ID":2846151,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.02418","arxiv_id":"2511.02418","title":"Biomolecular LQR under Partial Observation","abstract":"This paper introduces a biomolecular Linear Quadratic Regulator (LQR) to investigate the design principles of gene regulatory networks. We show that for fundamental gene regulation network, the bio-controller derived from LQR theory precisely recapitulate natural network motifs, such as auto-regulation and incoherent feedforward loops. This emulation arises from a fundamental principle: the LQR cost function mathematically encodes environmental survival demands, which subsequently drives the selection of both network topology and biochemical parameters. Our work thus establishes a theoretical basis for interpreting biological circuit design, directly linking evolutionary pressures to observable regulatory structures.","short_abstract":"This paper introduces a biomolecular Linear Quadratic Regulator (LQR) to investigate the design principles of gene regulatory networks. We show that for fundamental gene regulation network, the bio-controller derived from LQR theory precisely recapitulate natural network motifs, such as auto-regulation and incoherent f...","url_abs":"https://arxiv.org/abs/2511.02418","url_pdf":"https://arxiv.org/pdf/2511.02418v1","authors":"[\"Xiaoyu Zhang\",\"Zhou Fang\"]","published":"2025-11-04T09:47:45Z","proceeding":"q-bio.MN","tasks":"[\"q-bio.MN\",\"math.OC\"]","methods":"[]","has_code":false}