K-Means clustering for DNA computing readout method implemented on lightcycler system
In the previous paper, a readout approach for the Hamiltonian Path Problem (HPP) in DNA computing based on the real-time polymerase chain reaction (PCR) was proposed. Based on this approach, real-time amplification was performed with the TaqMan probes and the TaqMan detection mechanism was exploited...
محفوظ في:
| المؤلفون الرئيسيون: | , , , |
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| التنسيق: | Conference or Workshop Item |
| اللغة: | English |
| منشور في: |
2009
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://eprints.utm.my/id/eprint/12646/1/MuhammadFaizMohamed2008_KMeansClusteringforDNAComputingReadout.pdf http://eprints.utm.my/id/eprint/12646/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:99309 |
| الوسوم: |
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| الملخص: | In the previous paper, a readout approach for the Hamiltonian Path Problem (HPP) in DNA computing based on the real-time polymerase chain reaction (PCR) was proposed. Based on this approach, real-time amplification was performed with the TaqMan probes and the TaqMan detection mechanism was exploited for the design and development of the readout approach. The readout approach consists of two steps: real-time amplification in vitro using TaqMan-based real-time PCR, followed by information processing in silico to assess the results of real-time ampUfication, which in turn, enables extraction of the Hamiltonian path. However, the previous method used manual classification of two different output reactions of real-time PCR. In this paper, K-means clustering algorithm is used to identify automatically two different reactions in real-time PCR. It is shown that K-means clustering technique can be implemented for clustering output results of DNA computing readout method based on LightCycler System |
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