BIOSYSTEMS SCISCIE

中文简介

生物系统鼓励将生物学、进化思维和信息处理科学联系起来的实验、计算和理论文章。链接区域形成一个圆,包括生物信息处理的基本性质、计算复杂生物系统的建模,进化计算模型,应用生物原理的设计新颖的计算系统,以及利用生物分子材料的合成人工系统,捕捉自然生物信息处理的基本原则。下面列出的类别和主题都是例子，编辑们会很乐意就其他主题的相关性发表意见:分子进化自我组织和自我复制系统遗传机制的起源和演化生物信息处理分子识别细胞的控制Neuromolecular计算生物适应性分子计算技术进化系统随机进化算法进化优化遗传和生态系统的模拟应用(神经网络，机器学习，机器人)

投稿网址：http://ees.elsevier.com/bio/

英文简介

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)