ArticleBiotechnology journal2009
Production of random DNA oligomers for scalable DNA computing.
Article in Biotechnology journal, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
- Erratum issuedAustin, Alan [corrected to Austin, Allen]
Authors and funding
12 authors.
Funding
Abstract
While remarkably complex networks of connected DNA molecules can form from a relatively small number of distinct oligomer strands, a large computational space created by DNA reactions would ultimately require the use of many distinct DNA strands. The automatic synthesis of this many distinct strands is economically prohibitive. We present here a new approach to producing distinct DNA oligomers based on the polymerase chain reaction (PCR) amplification of a few random template sequences. As an example, we designed a DNA template sequence consisting of a 50-mer random DNA segment flanked by two 20-mer invariant primer sequences. Amplification of a dilute sample containing about 30 different template molecules allows us to obtain around 10(11) copies of these molecules and their complements. We demonstrate the use of these amplicons to implement some of the vector operations that will be required in a DNA implementation of an analog neural network.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.