Earticle

초록

영어

DNA computing is a computing paradigm as information storage media and information processing operators. Especially, information processing of DNA computing has emerged for gene expression pattern analysis and disease diagnosis. Recently, we developed a theoretical model for pattern classification, biomolecular perceptron. In the model, each pattern is a solution of various nucleotide strands. The patterns of the DNA species are summed with corresponding weight factors, where the result is used for the pattern’s classification. The calculation of this weighted summation is performed via competitive hybridization reactions between input molecules and differentially labeled probe molecules (molecular beacon), and the calculation is detected as fluorescence signals. Here, we demonstrate the experimental feasibility of pattern classification. We perform disease type discrimination using the subsequence of the acute leukemia marker genes. The results show the possibility of our method as a pattern classification
tool and diagnosis tool using gene expression. Because of the absence of information conversion steps, diagnosis process can be simplified.

저자

• Seung Hwan Lee [ School of Chemical and Biological Engineering ]
• Hee-Woong Lim [ School of Computer Science and Engineering Seoul National University ]
• Kyung-Ae Yang [ School of Computer Science and Engineering Seoul National University ]
• Suk-In Yoo [ School of Computer Science and Engineering Seoul National University ]
• Byoung-Tak Zhang [ School of Computer Science and Engineering Seoul National University ]
• Tai Hyun Park [ School of Chemical and Biological Engineering ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국생물공학회 학술대회

• 간기

  반년간

• 수록기간

  1985~2013

• 십진분류

  KDC 476 DDC 576