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First DNA-based Artificial Neural Network
Caltech researchers have demonstrated a small, four-cell neural network capable of simple problem-solving. This DNA-based artificial neural network uses DNA strand displacement cascades to recognize patterns in molecular events.

(DNA-based artificial neural network)
The neural network is made up of just four artificial neurons, as opposed to the human brain's 100 billion real ones.
To test the network, the scientists played a game with it. That game started with the network being trained to "know" four scientists, each one identifiable by a unique combination of yes/no answers to the same four questions (such as "Is the scientist British?"). Human players then chose one of those scientists, and provided the network with an incomplete set of the identifying answers. They did this by dropping DNA strands that were programmed to correspond to those answers, into water in a test tube that contained the neurons.
Communicating through fluorescent signals, the network would then either correctly identify the chosen scientist, it would indicate that it didn't have enough data to identify just one scientist, or it would state that the data didn't match any of the scientists.
This technology may one day give us intellectual cells like the ones in Greg Bear's excellent 1984 novel Blood Music:
His first E. coli mutations had had the learning capacity of planarian worms; he had run them through simple T-mazes, giving sugar rewards. They had soon outperformed planaria...
Removing the finest biologic sequences from the altered E. coli, he had incorporated them into B-lymphocytes, white cells from his own blood...Using artificial proteins and hormones as a means of communication, Vergil had "trained" the lymphocytes in the past six months to interact as much as possible with each other and with their environment - a much more complex miniature glass maze.
For now, the computational process is not quite up to the speed of silicon; the network takes about eight hours to respond.
From Nature via Gizmag.
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