| Info. | Vol.7 - No.1 (2013.03.20) |
|---|---|
| Title | Rule-based in vitro molecular classification and visualization |
| Authors | Soo-Yong Shin1,??/sup>, Kyung-Ae Yang2,??/sup>, In-Hee Lee2, Seung Hwan Lee3, Tai Hyun Park3 & Byoung-Tak Zhang2 |
| Institutions | 1Department of Biomedical Informatics, Asan Medical Center, and University of Ulsan College of Medicine, 43 Olympicro, Songpa-gu, Seoul 138-736, Korea
2Department of Computer Science and Engineering, Seoul National University, 599 Gwanangro, Gwanak-gu, Seoul 151-742, Korea 3School of Chemical and Biological Engineering, Bio-MAX Institute, Seoul National University, 599 Gwanangro, Gwanak-gu, Seoul, 151-742, Korea |
| Abstract | Molecular computing using programmable nucleic acids has been attracting attention for use in autonomous sensing systems and information processing systems by interacting with a biological environment. Here, we introduce a rule based in vitro molecular classification system that can classify disease patterns using several microRNA (miRNA) markers via the assembly of programmed DNA strands. The classification rules were derived by analyzing large-scale miRNA expression data obtained from a public database, and the identified rules were converted into DNA sequences. Classification was performed via the detection of miRNA markers in the rules. The classification results were reported as a binary output pattern according to their hybridization to the rule sequences, which can be conveniently visualized using gold nanoparticle aggregation. Our results demonstrate the utility of in vitro molecular classification by illustrating one of the ways in which molecular computing can be used in future biological and medical applications. |
| Keyword | In vitro classification, Molecular classification, DNA computing, Nanoparticle self assembly, Rule-based system |
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