It looks like you're using an Ad Blocker.
Please white-list or disable AboveTopSecret.com in your ad-blocking tool.
Some features of ATS will be disabled while you continue to use an ad-blocker.
Biologists have created a living computer from E. coli bacteria that can solve complex mathematical problems
Computers are evolving – literally. While the tech world argues netbooks vs notebooks, synthetic biologists are leaving traditional computers behind altogether. A team of US scientists have engineered bacteria that can solve complex mathematical problems faster than anything made from silicon. The research, published today in the Journal of Biological Engineering, proves that bacteria can be used to solve a puzzle known as the Hamiltonian Path Problem. Imagine you want to tour the 10 biggest cities in the UK, starting in London (number 1) and finishing in Bristol (number 10). The solution to the Hamiltonian Path Problem is the the shortest possible route you can take. This simple problem is surprisingly difficult to solve. There are over 3.5 million possible routes to choose from, and a regular computer must try them out one at a time to find the shortest. Alternatively, a computer made from millions of bacteria can look at every route simultaneously. The biological world also has other advantages. As time goes by, a bacterial computer will actually increase in power as the bacteria reproduce.
Originally posted by affeyee
reply to post by Alaskan Man
i wonder what is the difference between this mathematical calculation and the algorithm used for calculating network route call OSPF (open shortest path first) ??
anyone maths genius here ?
Choose a node to be the source or starting point.
Initialize source to 0 cost and mark as evaluated.
Initialize all nodes to infinite cost from the source.
For each node, y, adjacent to source
Relax the node. That is, set y's cost to the cost of all edges from source to y.
Place y into a priority queue based on its total cost. (Lower is better)
Add source node as predecessor of y.
While there are nodes in the graph that haven't been evaluated
Remove a node, x, from the PQ (lowest total cost)
Mark x as evaluated.
For each neighbor, y, of x
If new cost to reach y is less
Update list of nodes (path) to y from source.
Place y in the PQ.