Evangelizing Mainframe
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Biological Computers

Resistors and transistors, etc., have been with us for 70 years (give or take), but biological systems have been on this planet for more than 3.5 billion years. So it’s well proven they’re no flash in the pan, and there might be some things we could learn from living organisms. And various ideas about biological computers are being proposed.

Miguel Pais-Vieira, Mikhail Lebedev, Carolina Kunicki, Jing Wang and Miguel A.L. Nicolelis published an article titled, “A Brain-to-Brain Interface for Real-Time Sharing of Sensorimotor Information,” in Scientific Reports (Nature Publishing Group) in February 2013. They developed a brain-to-brain interface (BTBI) that enabled the real-time transfer of behaviorally meaningful sensorimotor information between the brains of two rats. What they did was to get an “encoder” rat to perform sensorimotor tasks that required it to make a choice from two tactile or visual stimuli. While this first rat performed the task, samples of its cortical activity were transmitted to matching cortical areas of a “decoder” rat using what’s called intracortical microstimulation (ICMS). The second rat learned to make similar behavioral selections, guided solely by the information provided by the first rat’s brain. The results show that a complex system was formed by coupling the animals’ brains. And this leads to the idea that BTBIs can enable dyads or networks of animals’ brains to exchange, process and store information and, hence, act like a biological computing device.

In the May 2013 edition of the Chemistry & Biology journal, professor Ehud Keinan of the Technion-Israel Institute of Technology, Tamar Ratne, Ron Piran and Natasha Jonoska published that a biological computer can be built using only biomolecules like enzymes and DNA. Their device can compute iteratively, which means it can use the output from one computation as a new input for subsequent computations, and it produces outputs in the form of biologically meaningful phenomena, such as resistance of bacteria to various antibiotics. So far, their transducer has performed a long division of binary numbers by three and an iterative computation. They suggest:

“The main advantages of biomolecular computing devices over the electronic computers arise from other properties. As shown in this work and other projects carried out in our lab, these systems can interact directly with biological systems and even with living organisms. No interface is required since all components of molecular computers, including hardware, software, input and output, are molecules that interact in solution along a cascade of programmable chemical events.”

Back in 1999, professor Bill Ditto from the Georgia Institute of Technology was using neurons from leeches to create a biological computer. The device could perform simple sums, so the team nicknamed it the “leech-ulator.” The device was meant to be able to think for itself because the leech neurons were able to form their own connections from one to another. Obviously, silicon-chip computers only make the connections they’re built with. This flexibility, Ditto explained, means the biological computer works out its own way of solving the problem.

Also published recently was news that Stanford University bioengineers Jerome Bonnet, Peter Yin, Monica E. Ortiz, Pakpoom Subsoontorn and Drew Endy have created the first biological transistor made from genetic materials—DNA and RNA. They claim their “transcriptor” is the final component required to build biological computers that operate inside living cells. What they’re proposing are biological computers that can detect changes in a cell’s environment, store a record of that change in memory made of DNA, and then trigger a response (such as self-destruction—apoptosis—if cancer is detected). Like a transistor controls the flow of electricity, this transcriptor will control the flow of RNA polymerase as it travels along a strand of DNA. The transcriptors do this by using special combinations of enzymes (called integrases) that control the RNA’s movement along the strand of DNA.

Last year, George Church and Sri Kosuri at Harvard’s Wyss Institute stored 5.5 petabits of data in a single gram of DNA.

Yes, I know it’s a far cry from an IBM mainframe running transactions against an IMS database for a Fortune 500 company. And it’s still a long way from being available from a shop near you. But it’s interesting to see what other computing ideas are running in parallel with big data, cloud computing and the “Internet of Things.”

Trevor Eddolls is CEO at iTech-Ed Ltd., an IT consultancy. For many years, he was the editorial director for Xephon’s Update publications and is now contributing editor to the Arcati Mainframe Yearbook. Eddolls has written three specialist IT books, and has had numerous technical articles published. He currently chairs the Virtual IMS and Virtual CICS user groups.

Posted: 6/25/2013 1:01:01 AM by Trevor Eddolls

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