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    • 21. 发明申请
    • GENOME-SCALE BUTANOL-PRODUCING MICROORGANISM METABOLIC NETWORK MODEL AND METHODS USING THE SAME FOR ANALYSIS OF METABOLIC CHARACTERISTICS OF BUTANOL-PRODUCING MICROORGANISMS AND FOR SCREENING DELETION TARGETS
    • 基因组规模的丁醇生产微生物代谢网络模型及其方法用于分析丁醇生产微生物的代谢特征和筛选减少目标
    • WO2009128644A3
    • 2010-01-21
    • PCT/KR2009001923
    • 2009-04-14
    • KOREA ADVANCED INST SCI & TECHBIOFUELCHEM COGS CALTEX CORPLEE SANG YUPLEE JOUNG MINYUN HONG SEOKJUNG KWANG SEOP
    • LEE SANG YUPLEE JOUNG MINYUN HONG SEOKJUNG KWANG SEOP
    • C12Q1/32
    • G01N33/569C12Q1/32C12Q1/527
    • The present invention relates to a metabolic network model for analysis of metabolic characteristics of butanol-producing microorganisms and methods using the same for analysis of metabolic characteristics of butanol-producing microorganisms and for screening deletion targets; and, more particularly, to establishing a metabolic network model of butanol-producing microorganisms using gene-protein-biochemical reaction associations and methods for analysis of metabolic characteristics such as a metabolic flow, etc., using the established model and for screening deletion targets with a simulation based on the metabolic flow analysis to improve the productivity of a specific metabolic product during the deletion. A metabolic network model according to the invention is useful for analysis of metabolic characteristics such as a metabolic flow, etc. of butanol-producing microorganisms and for screening a deletion target enzyme or a gene therefor to increase the production of a specific metabolic product. Moreover, unlike conventional methods, a deletion target screening method according to the invention makes it possible to predict deletion targets in an efficient manner, to save time and costs and to provide mutant microorganisms capable of producing a specific metabolic product at a high efficiency.
    • 本发明涉及用于分析丁醇生产微生物的代谢特征的代谢网络模型和使用其的丁醇生产微生物的代谢特征分析和筛选缺失目标的方法; 并且更具体地,涉及使用基因 - 蛋白质 - 生物化学反应关联建立丁醇生产微生物的代谢网络模型以及使用所建立的模型分析代谢流动等代谢特征的方法,并且用 基于代谢流分析的模拟以提高缺失期间特定代谢产物的生产力。 根据本发明的代谢网络模型可用于分析丁醇生产微生物的代谢特征如代谢流等,并用于筛选缺失目标酶或其基因以增加特定代谢产物的产生。 此外,与常规方法不同,根据本发明的缺失靶标筛选方法使得有可能以有效的方式预测缺失靶标,节省时间和成本并且提供能够高效生产特定代谢产物的突变微生物。
    • 24. 发明申请
    • MUTANT MICROORGANISM HAVING A HYDROCARBON-GENERATING ABILITY AND METHOD FOR PRODUCING HYDROCARBON USING SAME
    • 具有烃生产能力的突变微生物和使用其生产烃类的方法
    • WO2011155799A2
    • 2011-12-15
    • PCT/KR2011004289
    • 2011-06-10
    • KOREA ADVANCED INST SCI & TECHLEE SANG YUPCHOI YONG JUN
    • LEE SANG YUPCHOI YONG JUN
    • C12N1/21C12N15/52C12P5/00
    • C12P5/00C07K14/245C12N9/001C12N9/18C12N9/88C12N9/93C12N15/52C12N15/70C12P5/005C12P5/02C12P5/026
    • The present invention relates to a mutant microorganism having the ability to generate hydrocarbon containing alkanes and to a method for producing hydrocarbons containing alkanes using the same. More particularly, the present invention relates to a mutant microorganism in which genes that code for enzymes for converting fatty acyl-acps to free fatty acids, genes that code for enzymes for converting free fatty acids to fatty acyl-CoA, genes that code for enzymes for converting fatty acyl-CoA to fatty aldehydes, and genes that code for enzymes for converting fatty aldehydes to alkanes are introduced to the microorganisms improved to be appropriate for the production of hydrocarbons containing alkanes. The present invention also relates to a method for producing hydrocarbons containing alkanes. The mutant microorganism according to the present invention has a high possibility of being utilized in strain improvement resulting from an additional metabolic control, and therefore, can be valuably used in the industrial production of hydrocarbons containing alkanes.
    • 本发明涉及具有产生含烃烷烃的能力的突变微生物以及使用其的烷烃生产烃的方法。 更具体地说,本发明涉及一种突变体微生物,其中编码用于将脂肪酰基 - 脯氨酸转化为游离脂肪酸的酶的基因,编码用于将游离脂肪酸转化成脂肪酰基-CoA的酶的基因,编码酶的基因 用于将脂肪酰基辅酶A转化成脂肪醛,并且将用于将脂肪醛转化为烷烃的酶编码的基因被引入微生物以改进以适合于生产含烷烃的烃。 本发明还涉及一种生产含烷烃的烃的方法。 根据本发明的突变体微生物具有很高的可能性,用于由额外的代谢控制引起的应变改善,因此可以有价值地用于工业生产含烃烷烃。
    • 28. 发明申请
    • BIOSENSOR USING CONDUCTIVE GRAPHENES AND PREPARATION METHOD THEREOF
    • 使用导电石墨的生物传感器及其制备方法
    • WO2009157739A3
    • 2010-04-01
    • PCT/KR2009003482
    • 2009-06-26
    • KOREA ADVANCED INST SCI & TECHLEE SANG YUPPARK TAE JUNGHONG WON HIJUNG HEE TAEPARK HO SEOKCHOI BONG GILL
    • LEE SANG YUPPARK TAE JUNGHONG WON HIJUNG HEE TAEPARK HO SEOKCHOI BONG GILL
    • C01B31/02
    • G01N33/5438B82Y30/00B82Y40/00C01B32/194C12Q1/004
    • The present invention relates to a biosensor using conductive graphenes and a preparation method thereof, and more particularly, to a biosensor and a preparation method thereof, which uses a conductive graphene prepared using chemical functional groups or a conductive graphine to which a bioreceptor is attached, the bioreceptor being selectively combined to a target biomaterial on a laminated conductive graphene film repeatedly overlaid with the conductive graphenes in order to have a high surface density on a substrate. The conductive graphene biosensor according to the present invention has a large surface area and excellent electric conductivity, and thus can increase the immobilization rate of biological molecules, such as DNA, and enhance the detection sensitivity for biological molecules. In addition, by either directly detecting various target biomolecules or detecting electrochemical signals, the present invention can accurately detect reactions of biomaterials and bioreceptors on a large scale at once, and can introduce a detection method by which an accurate measurement, even of a small amount of source, can be obtained.
    • 本发明涉及一种使用导电石墨烯的生物传感器及其制备方法,更具体地说,涉及一种生物传感器及其制备方法,该生物传感器及其制备方法使用使用化学官能团或连接有生物受体的导电石墨制备的导电石墨烯, 生物受体被选择性地组合到层叠的导电石墨烯膜上的目标生物材料上,所述层压导电石墨烯膜与导电石墨烯重复地重叠以在基底上具有高的表面密度。 根据本发明的导电石墨烯生物传感器具有大的表面积和优异的导电性,因此可以增加DNA等生物分子的固定化率,提高生物分子的检测灵敏度。 另外,通过直接检测各种目标生物分子或检测电化学信号,本发明可以一次性地大规模地精确地检测生物材料和生物感应器的反应,并且可以引入检测方法,通过该方法进行精确的测量,甚至少量 的来源,可以获得。
    • 30. 发明申请
    • GENOME-SCALE BUTANOL-PRODUCING MICROORGANISM METABOLIC NETWORK MODEL AND METHODS USING THE SAME FOR ANALYSIS OF METABOLIC CHARACTERISTICS OF BUTANOL-PRODUCING MICROORGANISMS AND FOR SCREENING DELETION TARGETS
    • 基因组大肠杆菌生产微生物代谢网络模型及其使用方法用于分析生产微生物的代谢特征和筛选目标的代谢特征
    • WO2009128644A2
    • 2009-10-22
    • PCT/KR2009001923
    • 2009-04-14
    • KOREA ADVANCED INST SCI & TECHBIOFUELCHEM COGS CALTEX CORPLEE SANG YUPLEE JOUNG MINYUN HONG SEOKJUNG KWANG SEOP
    • LEE SANG YUPLEE JOUNG MINYUN HONG SEOKJUNG KWANG SEOP
    • C12Q1/32
    • G01N33/569C12Q1/32C12Q1/527
    • The present invention relates to a metabolic network model for analysis of metabolic characteristics of butanol-producing microorganisms and methods using the same for analysis of metabolic characteristics of butanol-producing microorganisms and for screening deletion targets; and, more particularly, to establishing a metabolic network model of butanol-producing microorganisms using gene-protein-biochemical reaction associations and methods for analysis of metabolic characteristics such as a metabolic flow, etc., using the established model and for screening deletion targets with a simulation based on the metabolic flow analysis to improve the productivity of a specific metabolic product during the deletion. A metabolic network model according to the invention is useful for analysis of metabolic characteristics such as a metabolic flow, etc. of butanol-producing microorganisms and for screening a deletion target enzyme or a gene therefor to increase the production of a specific metabolic product. Moreover, unlike conventional methods, a deletion target screening method according to the invention makes it possible to predict deletion targets in an efficient manner, to save time and costs and to provide mutant microorganisms capable of producing a specific metabolic product at a high efficiency.
    • 本发明涉及用于分析产生丁醇的微生物的代谢特征的代谢网络模型,以及使用该代谢特征分析产生丁醇的微生物的代谢特征和筛选缺失目标的方法。 更具体地,使用基因 - 蛋白质 - 生物化学反应关联建立丁醇生产微生物的代谢网络模型,以及使用建立的模型分析代谢流动等的代谢特征的方法,并用于筛选具有 基于代谢流分析的模拟,以提高缺失期间特定代谢产物的生产力。 根据本发明的代谢网络模型可用于分析产生丁醇的微生物的代谢流等的代谢特征,并且用于筛选缺失目标酶或其基因以增加特定代谢产物的产生。 此外,与常规方法不同,根据本发明的缺失目标筛选方法使得有可能以有效的方式预测缺失目标,以节省时间和成本,并提供能够以高效率产生特定代谢产物的突变体微生物。