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微生物间的代谢相互作用在生物体内外的生态功能中起着关键作用。研究揭示了代谢模型在理解细菌共培养中竞争与合作动态的重要性，以及如何通过计算方法预测微生物相互作用。基因-基因交互作用在疾病遗传学中的角色也得到了深入探讨，提出新的基于熵和进化的方法。此外，微生物组学和生物信息学工具，如@MInter，用于自动提取微生物相互作用，促进了微生物群落研究的进展。
微生物交互关系研究论文摘要集锦
- 296. A computational exploration of bacterial metabolic diversity identifying metabolic interactions and growth-efficient strain communities
- 297. A Modified Entropy-Based Approach for Identifying Gene-Gene Interactions in Case-Control Study
- 298. A new mathematical model of bacterial interactions in two-species oral biofilms
- 299. A Novel Evolution-Based Method for Detecting Gene-Gene Interactions
- 300. Active learning for human protein-protein interaction prediction
- 115. @MInter: automated text-mining of microbial interactions.
- 301. Characterizing metabolic interactions in a clostridial co-culture for consolidated bioprocessing
- 302. Competition, Not Cooperation, Dominates Interactions among Culturable Microbial Species
- 7. Competitive and cooperative metabolic interactions in bacterial communities
- 65. Complex Species Interactions and the Dynamics of Ecological Systems: Long-Term Experiments
- 303. CompNet: a GUI based tool for comparison of multiple biological interaction networks
- 304. Computing paths and cycles in biological interaction graphs
- 305. Detecting temporal protein complexes from dynamic protein-protein interaction networks
- 306. Dynamical modeling of uncertain interaction-based genomic networks
- 307. Effective comparative analysis of protein-protein interaction networks by measuring the steady-state network flow using a Markov model
- 24. Elucidation of complexity and prediction of interactions in microbial communities
- 173. Establishment and metabolic analysis of a model microbial community for understanding trophic and electron accepting interactions of subsurface anaerobic environments
- 308. Exploring biological interaction networks with tailored weighted quasi-bicliques
- 309. Genome-based Modeling and Design of Metabolic Interactions in Microbial Communities
- 310. Global metabolic interaction network of the human gut microbiota for context-specific community-scale analysis
- 311. Host-Gut Microbiota Metabolic Interactions
- 312. Host-microbial interaction in the mammalian intestine and their metabolic role inside
- 313. Host-microbial interactions in the metabolism of therapeutic and diet-derived xenobiotics
- 314. Identification of novel metabolic interactions controlling carbon flux from xylose to ethanol in natural and recombinant yeasts
- 315. Inference of Network Dynamics and Metabolic Interactions in the Gut Microbiome
- 316. Inferring microbial interaction network from microbiome data using RMN algorithm
- 317. Inferring microbial interaction networks from metagenomic data using SgLV-EKF algorithm
- 318. Interaction networks for identifying coupled molecular processes in microbial communities
- 319. Large-scale in silico modeling of metabolic interactions between cell types in the human brain
- 320. Limitations of a metabolic network-based reverse ecology method for inferring host–pathogen interactions
- 321. Metabolic Interaction of Helicobacter pylori Infection and Gut Microbiota
- 322. Metabolic interactions in microbial communities: untangling the Gordian knot
- 323. Metabolic network analysis reveals microbial community interactions in anammox granules
- 324. MetaMIS: a metagenomic microbial interaction simulator based on microbial community profiles
- 325. Microbial interactions for enhancement of a-amylase production by Bacillus amyloliquefaciens 04BBA15 and Lactobacillus fermentum 04BBA19
- 326. Microbial interactions: from networks to models
- 327. MIMO: an efficient tool for molecular interaction maps overlap
- 328. MMinte: an application for predicting metabolic interactions among the microbial species in a community
- 48. Model-based quantification of metabolic interactions from dynamic microbial-community data
- 76. Multispecies communities: interspecies interactions influence growth on saliva as sole nutritional source.
- 329. PID: the Pathway Interaction Database
- 16. Predicting microbial interactions through computational approaches
- 330. The integrated analysis of metabolic and protein interaction networks reveals novel molecular organizing principles
- 14. The large-scale organization of the bacterial network of ecological co-occurrence interactions
- 331. The linear neighborhood propagation method for predicting long non-coding RNA –protein interactions
- 332. Understanding the interactions between bacteria in the human gut through metabolic modeling
- 333. Visualization of Metabolic Interaction Networks in Microbial Communities Using VisANT 5.0
- 364. Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections
- 366. Lotka-Volterra pairwise modeling fails to capture diverse pairwise microbial interactions
296. A computational exploration of bacterial metabolic diversity identifying metabolic interactions and growth-efficient strain communities
296.细菌代谢多样性识别代谢相互作用和高效生长菌株群落的计算性探索
摘要：背景：代谢相互作用涉及代谢产物在微生物物种之间的交换。大多数微生物生活在社区，通常依靠代谢相互作用来增加养分供应，更好地利用特定的环境。基于约束的模型已经成功地分析了细胞代谢并描述了基因型-表型关系。但是，对基因组规模的多种群相互作用的研究还很少。基于基因组规模的方法，我们提出一个图形理论的方法与代谢模型，以探讨细菌菌株之间的代谢变异性，并鉴定和描述代谢相互作用的菌株群落由两个或两个以上菌株组成的分批培养。我们证明了我们的方法在不同的单碳源条件下对细菌大肠杆菌的适用性。结果：为每个生长条件构建不同的多样性图。所构建的图的图论性质反映了细胞固有的高代谢冗余性以单基因敲除，揭示了关于副产物的独特代谢能力的突变体集合体，在各种条件下展
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