Protein Design: Automated protein discovery and synthesis

Written by Paras Chopra

Continued from page 1

4. Protein Printer This isrepparttar only hardware part ofrepparttar 140233 whole procedure. It will producerepparttar 140234 desired real proteins fromrepparttar 140235 amino acid sequence received from software. It may be able to work in any ofrepparttar 140236 two ways:

* Artificial Ribosome: It will mimicrepparttar 140237 functionality ofrepparttar 140238 cell to produce proteins. We will generate an mRNA using some assembling mechanism. Then, our artificially designed Ribosome will translate it into a protein which we can use. * Artificial Recombinant DNA: We will assemble a fragment of DNA corresponding to desired amino acid sequence. Then by using some automated means we will introducerepparttar 140239 DNA into a colony of E. coli (or some other organism)/ Then E. coli will produce these synthetic proteins inrepparttar 140240 same way they produce natural proteins in recombinant DNA technology.

5. Conclusion Using this system, we only need to define: "What do we wantrepparttar 140241 protein to do?". All other procedure is automatic. We just need to tell if we want a protein to degrade plastic, convert CO2 into diamond and oxygen, and catalyze/initiate cold fusion, etc. & we will have ready made proteins. It can also help in finding proteins which will help us attain Immortality.

The potential is immense. The only need is its correct use.

Paras Chopra was born in Patiala, Punjab, India on 3rd June 1987. His interests lie in subjects ranging from Nanotechnology to Biotechnology to Artificial Intelligence. His goal in life is to achieve immortality.

Visit him at:

Memory Research Misses The Obvious

Written by Abraham Thomas

Continued from page 1
Global applications. Combinatorial coding could provide immense intelligence torepparttar nervous system. The wonder of nature wasrepparttar 140135 enormous scale, scope and sensitivity of its reporting systems. The mind had this vast army of scouts, reporting back on millions of tiny sensations -repparttar 140136 heat of sun andrepparttar 140137 hardness of rock. Pain onrepparttar 140138 skin too was a report. When their impulses were received inrepparttar 140139 cortex, you felt pain. Inrepparttar 140140 earlier example, with combinatorial coding, a cell could fire for ABD and be inhibited for ABP. Ifrepparttar 140141 pain reporting nerve cell recognized inputs from its neighbours, it could also respond to neighbouring pain and fire to report sympathetic pain. It could respond to touch and inhibit its own sympathetic pain message. The cell could respond to context. Pattern recognition. Nerve cells didn't receive just a few inputs. They received thousands. So, pain could be sensitive to context. Inherited memories in combinatorial codes could enablerepparttar 140142 system to recognize and respond to patterns in context. Combinatorial coding could explainrepparttar 140143 mind as a pattern recognition engine. But science worked onrepparttar 140144 assumption thatrepparttar 140145 neurons inrepparttar 140146 brain did not recognize, but did computations. The search for a mathematical formula which could simulaterepparttar 140147 computations ofrepparttar 140148 mind goes on. But, if you assumed pattern recognition, you just stepped out ofrepparttar 140149 mathematical maze. Unfortunately,repparttar 140150 recognition of patterns was too formidable a task for computers. The diagnosis of diseases was a typical pattern recognition problem. The pattern recognition difficulty. The obstacle was that many shared symptoms were presented by different diseases. Pain, or fever were present for many diseases. Each symptom pointed to several diseases. Inrepparttar 140151 customary search,repparttar 140152 first selected disease withrepparttar 140153 first presented symptom could lackrepparttar 140154 second symptom. Sorepparttar 140155 back and forth searches followed an exponentially expanding trajectory asrepparttar 140156 database increased in size. That maderepparttar 140157 process absurdly long drawn – theoretically, even years, when searching extensive databases. Inrepparttar 140158 light of such an impregnable problem, science did not evaluate pattern recognition as a practical process forrepparttar 140159 nervous system. An instant pattern recognition process. There is an Intuitive Algorithm (IA), which follows a logical process to achieve real time pattern recognition. IA was unique. In a feat never achieved by computers before, IA could almost instantly diagnose diseases. IA used elimination to narrow down possibilities to reachrepparttar 140160 correct answer. In essence, IA did not calculate, but used elimination to recognize patterns. IA acted withrepparttar 140161 speed of a simple recalculation on a spreadsheet, to recognize a disease, identify a case law or diagnoserepparttar 140162 problems of a complex machine. It did this holistically and almost instantly, through simple, logical steps. IA proved that holistic, instant, real time pattern recognition was practical. IA provided a clue torepparttar 140163 secret of intuition. The website andrepparttar 140164 book explain IA in detail. Seamless pattern recognition. The mind was a recognition machine, which instantly recognizedrepparttar 140165 context of its ever changing environment. The system triggered feelings when particular classes of events were recognized. The process was achieved by inherited nerve cell memories accumulated across millions of years. The memories enabledrepparttar 140166 mind to recognized events. Similar inherited memories in nerve cells enabledrepparttar 140167 mind to trigger feelings, when events were recognized. And further cell memories caused feelings to trigger actions. Actions were sequences of muscle movements. Even drive sequences could be remembered by nerve cells. That was how we were driven. Sorepparttar 140168 circuit closed. Half a second for a 100 billion nerve cells to use context to eliminate irrelevance and deliver motor output. The time betweenrepparttar 140169 shadow andrepparttar 140170 scream. So, from input to output,repparttar 140171 mind was a seamless pattern recognition machine. Intuition and memory. Walter Freemanrepparttar 140172 famous neurobiologist definedrepparttar 140173 critical difficulty for science in understandingrepparttar 140174 mind. “The cognitive guys think it's just impossible to keep throwing everything you've got intorepparttar 140175 computation every time. But, that is exactly whatrepparttar 140176 brain does. Consciousness is about bringing your entire history to bear on your next step, your next breath, your next moment.” The mind was holistic. It evaluated all its knowledge forrepparttar 140177 next activity. However large its database,repparttar 140178 logic of IA could yield instant pattern recognition. Since that logic was robust and practical, intuition could also be such an instant pattern recognition process. Intuition could then powerrepparttar 140179 mind to instantly recognize an infinite variety of objects and events to trigger motor responses. Each living moment, it could evaluaterepparttar 140180 context of a dynamic multi-sensory world and its own vast memories. Those memories could be stored inrepparttar 140181 combinatorial codes of nerve cells.

Abraham Thomas is the author of The Intuitive Algorithm, a book, which suggests that intuition is a pattern recognition algorithm. The ebook version is available at The book may be purchased only in India. The website, provides a free movie and a walk through to explain the ideas.

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