BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.The categories and topics listed below are examples, the editors will be happy to comment on the relevance of other topics:Molecular EvolutionSelf-organizing and self-replicating systemsOrigins and evolution of the genetic mechanismBiological Information ProcessingMolecular recognitionCellular controlNeuromolecular computingBiological adaptabilityMolecular computing technologiesEvolutionary SystemsStochastic evolutionary algorithmsEvolutionary optimizationSimulation of genetic and ecological systemsApplications (neural nets, machine learning, robotics)

生物系統鼓勵將生物學、進化思維和信息處理科學聯系起來的實驗、計算和理論文章。鏈接區域形成一個圓,包括生物信息處理的基本性質、計算復雜生物系統的建模,進化計算模型,應用生物原理的設計新穎的計算系統,以及利用生物分子材料的合成人工系統,捕捉自然生物信息處理的基本原則。下面列出的類別和主題都是例子，編輯們會很樂意就其他主題的相關性發表意見:分子進化自我組織和自我復制系統遺傳機制的起源和演化生物信息處理分子識別細胞的控制Neuromolecular計算生物適應性分子計算技術進化系統隨機進化算法進化優化遺傳和生態系統的模擬應用(神經網絡，機器學習，機器人)