暴力分析，强行建模

实验室简介

课题组以生物系统中的自组织规律为核心研究方向，运用数据挖掘、网络动力学等计算方法，重点关注于如下领域：

• 微生物从演化到群落互作中的定量科学；
• 多细胞体系中模式生成的数学规律；
• 生物大数据挖掘的方法开发；
• 传染病动力学和非药物应对策略研究。

Our research focuses on the principles of self-organization in biological systems. Utilizing computational approaches such as data mining and network dynamics, we are particularly interested in:

• Quantitative microbial ecology, with emphasis on secondary metabolite evolution and ecological interactions;
• Mathematical rules underlying pattern formation in multicellular systems;
• Methodological development for biological big data mining;
• Dynamical modeling of infectious diseases and non-pharmaceutical interventions.

最新动态

基于基因组数据挖掘高效预测微生物铁载体互作网络

构建微生物铁互作网络的观点简述

利用超解景观构建细胞命运决策的整体图谱

干湿结合实验探索

为了从理论研究向实验验证转型，课题组以现有的铁载体网络成果为基础，开展了微生物培养、产物诱导、次级互作等实验探索，积极迈向干湿结合（dry-wet integration）实验室建设。

代表性文章

• Jeremy Howard* et al. (2020). Face masks against COVID-19: an evidence review. PNAS, 118(4), e2014564118.
• Zhiyuan Li et al. (2020). Modeling microbial metabolic trade-offs in a chemostat. PLOS Computational Biology, 16(8), e1008156.
• Jindong Zan*, Zhiyuan Li* et al. (2019). A microbial factory of defense chemicals in a tripartite marine symbiosis. Science, 364, 1056. DOI: 10.1126/science.aaw6732.
• Li, Sophia Hsin-Jung, Zhiyuan Li et al. (2018). Escherichia coli translation strategies differ across carbon, nitrogen and phosphorus limitation conditions. Nature Microbiology, 3(8): 939. DOI:10.1038/s41564-018-0199-2.
• Jian Shu*, Chen Wu*, Zhiyuan Li* et al. (2013). Induction of Pluripotency in Mouse Somatic Cells with Lineage Specifiers. Cell, 153(5), 963–975. DOI: 10.1016/j.cell.2013.05.001.