A Biomolecular Computing Model in Vivo for Minimum Dominating Set Problem

生物体内分子网络中信息的传输、储存、放大、整合等大量任务可以看成是一种生物分子计算过程.文中提出了一种活体分子计算模型,借助rnA干扰技术和乳糖操纵子调控模型,在细胞内构建了一个基因网络,用于求解图的最小支配集.该模型展示了利用生物体自身的信息处理能力进行计算的能力,在生物体内建立具有一定智能的分子机器,这将在计算科学、生物学、医学上有着深远的应用前景.Biomolecular computing models in vivo are an emerging computing model inspired from the biological phenomena that the biochemical molecular in living perform computation,communications,and signal processing collaboratively.In this paper,a biomolecular computing model in vivo for minimum dominating set problem is presented,a synthetic gene network is constructed by RNAi and lactose operon in living cell.This model explores further the ability to solve hard problems based on organism processing signal,and try to construct an intelligent molecule machine in cell.It may be widely and further used in computing science,biology,and medicine.国家自然科学基金(60910002;60974112;60971085;30970969);国家“八六三”高技术研究发展计划项目基金(2009AA012413);教育部博士点基金(20070001020);中国博士后基金(20080440257)资

学前儿童分类能力再探

本研究分别以3×3类的两级层次水平类概念刺激物让4—6岁儿童作自由分类。结果表明,即使4岁儿童大部分也能按基本概念标准分类并能作词概括,能正确按上级类概念标准独立分类的被试人数随年龄而增多。儿童分类能力的发展依存于主体抽象概括的思惟发展水平;对类概念标志词的掌握,其它概念组织的竞争,以及刺激物的数量和性质等也是影响分类作业成绩的因素