Earticle

초록

영어

There have been several systematic approaches to identify novel synthetic pathways in the metabolic network. However, the prediction was too general or too specified. To achieve both of generality and specificity of the prediction at a reliable level, we propose a systematic approach
and related framework. To allow applications, five factors that can affect the novel pathways were considered. Three types of abilities, such as similarity, thermodynamics, and co-expression, are evaluated. The five factors are binding site covalence, chemical similarity, thermodynamic favorability, pathway distance, and organism specificity. We suggest a
method to evaluate these factors and calculate priority scores which rank the detected candidates. The factors are evolutionary optimized, and thus the system evolves itself. Our approach will enhance the production of desired biochemicals. [This work was supported by the
Korean Systems Biology Research Program (M10309020000-03B5002- 00000) of the Ministry of Education, Science and Technology (MEST). Further supports by LG Chem Chair Professorship, Microsoft, World Class University Program of MEST and IBM-SUR program are greatly appreciated.]

키워드

저자

• Ryeojin LEE [ Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical & Biomolecular Engineering (BK21 Program),,KAIST ]
• Ayoun CHO [ Process Systems Laboratory, Department of Chemical & Biomolecular Engineering (BK21 Program),, KAIST ]
• Hongseok YUN [ Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical & Biomolecular Engineering (BK21 Program),,KAIST ]
• Sang Yup LEE [ Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical & Biomolecular Engineering (BK21 Program),,KAIST ]
• Sunwon PARK [ Process Systems Laboratory, Department of Chemical & Biomolecular Engineering (BK21 Program),, KAIST ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국생물공학회 학술대회

• 간기

  반년간

• 수록기간

  1985~2013

• 십진분류

  KDC 476 DDC 576