Literature DB >> 17292083

Estimating the sequence complexity of a random oligonucleotide population by using in vitro thermal melting and Cot analyses.

Jin-Woo Kim1, Dylan P Carpenter, Russell Deaton.   

Abstract

Randomly generated oligonucleotide populations have a high potential to serve as pools for selecting non-cross-hybridizing sequences, which are useful for nanoscale self-assembly and biological and biomedical applications, as well as for DNA computing applications. In this study a nonlinear kinetic model was developed for the complexity estimation of large unknown polynucleotide populations and was experimentally verified. The model was implemented to estimate the sequence complexity of the random 20 base-pair population after in vitro renaturation experiments. The kinetic behaviors of the random 20mers were also evaluated with in vitro thermal melting experiments. This study represents a step in realizing the potential of random oligonucleotides for DNA computing and nanoscale self-assembly applications for biology and medicine.

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Year:  2005        PMID: 17292083     DOI: 10.1016/j.nano.2005.06.003

Source DB:  PubMed          Journal:  Nanomedicine        ISSN: 1549-9634            Impact factor:   5.307


  1 in total

1.  A DNA-based pattern classifier with in vitro learning and associative recall for genomic characterization and biosensing without explicit sequence knowledge.

Authors:  Ju Seok Lee; Junghuei Chen; Russell Deaton; Jin-Woo Kim
Journal:  J Biol Eng       Date:  2014-11-06       Impact factor: 4.355

  1 in total

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