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Titlebook: DNA Computing; 7th International Wo Nata?a Jonoska,Nadrian C. Seeman Conference proceedings 2002 Springer-Verlag Berlin Heidelberg 2002 Bio

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61#
發(fā)表于 2025-4-1 05:17:37 | 只看該作者
62#
發(fā)表于 2025-4-1 07:55:50 | 只看該作者
Population Computation and Majority Inference in Test Tube number of DNA strands in the test tube and a probabilistic logical inference based on the probabilistic interpretation. Second, in order for the DNA-based learning algorithm [.] to be robust for errors in the data, we implement the weighted majority algorithm [.] on DNA computers, called . (DNAMA),
63#
發(fā)表于 2025-4-1 11:23:30 | 只看該作者
DNA Starts to Learn Poker) to wait your turn, (2) to default to the most conservative course, (3) to probabilistically override the default in some cases, and (4) to learn from payoffs. Two players each use an independent population of strategies that adapt and learn from their experiences in competition.
64#
發(fā)表于 2025-4-1 14:35:08 | 只看該作者
PNA-mediated Whiplash PCR. A barrier confronting efficient implementation, however, is a systematic tendency for encoded molecules towards backhybridization, a simple form of self-inhibition. In order to examine this effect, the length distribution of extended strands over the course of the reaction is examined by modeling
65#
發(fā)表于 2025-4-1 18:43:07 | 只看該作者
Biomolecular Computation in Virtual Test Tubesomputational purposes. While biomolecules have resolved fundamental problems as a parallel computer system that we are just beginning to decipher, BMC still suffers from our inability to harness these properties to bring biomolecular computations to levels of reliability, efficiency and scalability
66#
發(fā)表于 2025-4-1 23:59:17 | 只看該作者
67#
發(fā)表于 2025-4-2 03:19:38 | 只看該作者
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