Using a PCR‐Based Method To Analyze and Model Large, Heterogeneous Populations of DNA †
Abstract: The study of populations of large size and high diversity is limited by the capability of collecting data. Moreover, for a pool of individuals, each associated with a unique characteristic feature, as the pool size grows, the possible interactions increase exponentially and quickly go beyond the limit of computation and experimental studies. Herein, the design of DNA libraries with various diversity is reported. By using a facile analytical method based on real‐time PCR, the diversity of a pool of DNA can be evaluated to allow extraordinarily high heterogenicity (e.g., >1 trillion). It is demonstrated that these DNA libraries can be used to model heterogeneous populations; these libraries exhibit functions such as self‐protection, suitability for biased expansion, and the possibility to evolve into amorphous structures. The method has shown the remarkable power of parallel computing with DNA, since it can resemble an analogue computer and be applied in selection‐based biotechnology methods, such as DNA‐encoded chemical libraries. As a chemical approach to solve problems traditionally for genetic and statistical analysis, the method provides a quick and cost‐efficient evaluation of library diversity for intermediate steps through a selection process.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Using a PCR‐Based Method To Analyze and Model Large, Heterogeneous Populations of DNA † ; volume:21 ; number:8 ; year:2020 ; pages:1144-1149 ; extent:6
ChemBioChem ; 21, Heft 8 (2020), 1144-1149 (gesamt 6)
- Urheber
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Andrade, Helena
Thomas, Alvin K.
Lin, Weilin
Reddavide, Francesco V.
Zhang, Yixin
- DOI
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10.1002/cbic.201900603
- URN
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urn:nbn:de:101:1-2022062212251289781738
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:22 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Andrade, Helena
- Thomas, Alvin K.
- Lin, Weilin
- Reddavide, Francesco V.
- Zhang, Yixin
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