Difference between revisions of "Team:SEU/Contribution"

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               <p>BioBricks uses DNA fragments to build blocks to systematically assemble new organisms and other biologically related components. BioBricks uses DNA as a genetic information base to construct targeted organisms.</p>
 
               <p>BioBricks uses DNA fragments to build blocks to systematically assemble new organisms and other biologically related components. BioBricks uses DNA as a genetic information base to construct targeted organisms.</p>
 
               <p>In this experiment, we also use DNA as the basic material, but unlike the functions of DNA mentioned above, DNA no longer plays a role of genetic material in the experiment. We take the structure and properties of DNA as the precondition of constructing neural network, destroy the hydrogen bond between DNA double strands by heating, and then reassemble the corresponding fragments through annealing operation to achieve the effect of chain-to-chain replacement.</p>
 
               <p>In this experiment, we also use DNA as the basic material, but unlike the functions of DNA mentioned above, DNA no longer plays a role of genetic material in the experiment. We take the structure and properties of DNA as the precondition of constructing neural network, destroy the hydrogen bond between DNA double strands by heating, and then reassemble the corresponding fragments through annealing operation to achieve the effect of chain-to-chain replacement.</p>
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               <p>In the process of experiment, by controlling the reaction conditions, changing the reaction rate and environment, and according to the specificity of pairing between DNA single strands, we can realize the function of inputting a single strand of DNA and then outputting a specific single strand of DNA. We have successfully constructed a neural network and provided an effective way to customize a specific single strand of DNA. This method expands the idea of using DNA. DNA can perform more diverse tasks through the specificity of DNA base pairing.
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               <p>In the process of experiment, by controlling the reaction conditions, changing the reaction rate and environment, and according to the specificity of pairing between DNA single strands, we can realize the function of inputting a single strand of DNA and then outputting a specific single strand of DNA. We have successfully constructed a neural network and provided an effective way to customize a specific single strand of DNA. This method expands the idea of using DNA. DNA can perform more diverse tasks through the specificity of DNA base pairing.</p>
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<blockquote><p>Optimizing Artificial Intelligence Network.</p></blockquote>
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  报错</p>
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               <p>It is worth mentioning that we have constructed an efficient artificial neural network, which can prepare specific DNA single strands and show great potential in biology and medical biological information processing. Different from the general artificial neural network, our artificial neural network achieves back propagation. According to the output of the neural network, we can adjust the input parameters accordingly, and then optimize the next output, and finally get more stable output in line with our expectations. This method of continuous optimization using feedback results is not involved in the previous artificial neural network, which is also the advantage of our model..</p>
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               <p>Duis autem vel eum iriure dolor in hendrerit in vulputate velit esse molestie consequat, vel illum dolore eu feugiat nulla facilisis at vero eros et accumsan et iusto odio dignissim qui blandit praesent luptatum zzril.</p>
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<blockquote><p>Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet vultatup duista.</p></blockquote>
 
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Revision as of 16:25, 28 September 2019

Collaboration

Through the comprehensive use of life science and information science knowledge, we have obtained the results of this experiment. In the whole process, we encountered many difficulties and challenges, but after careful thinking and practice, we finally successfully overcome these. In addition, we have also summarized some information that may be helpful to other teams, hoping to make some contributions to the iGEM community.

New method of using DNA

In the experiment, we take the complementary matching principle of single stranded DNA bases as the basis of experiment and theory, which is similar to the function of BioBricks, but different.

BioBricks uses DNA fragments to build blocks to systematically assemble new organisms and other biologically related components. BioBricks uses DNA as a genetic information base to construct targeted organisms.

In this experiment, we also use DNA as the basic material, but unlike the functions of DNA mentioned above, DNA no longer plays a role of genetic material in the experiment. We take the structure and properties of DNA as the precondition of constructing neural network, destroy the hydrogen bond between DNA double strands by heating, and then reassemble the corresponding fragments through annealing operation to achieve the effect of chain-to-chain replacement.

In the process of experiment, by controlling the reaction conditions, changing the reaction rate and environment, and according to the specificity of pairing between DNA single strands, we can realize the function of inputting a single strand of DNA and then outputting a specific single strand of DNA. We have successfully constructed a neural network and provided an effective way to customize a specific single strand of DNA. This method expands the idea of using DNA. DNA can perform more diverse tasks through the specificity of DNA base pairing.

Optimizing Artificial Intelligence Network.

It is worth mentioning that we have constructed an efficient artificial neural network, which can prepare specific DNA single strands and show great potential in biology and medical biological information processing. Different from the general artificial neural network, our artificial neural network achieves back propagation. According to the output of the neural network, we can adjust the input parameters accordingly, and then optimize the next output, and finally get more stable output in line with our expectations. This method of continuous optimization using feedback results is not involved in the previous artificial neural network, which is also the advantage of our model..

Heading 1

Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet vultatup duista.

Duis autem vel eum iriure dolor in hendrerit in vulputate velit esse molestie consequat, vel illum dolore eu feugiat nulla facilisis at vero eros et accumsan et iusto odio dignissim qui blandit praesent luptatum zzril.

Heading 1

Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet vultatup duista.

Duis autem vel eum iriure dolor in hendrerit in vulputate velit esse molestie consequat, vel illum dolore eu feugiat nulla facilisis at vero eros et accumsan et iusto odio dignissim qui blandit praesent luptatum zzril.

Heading 1

Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.

Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.

  1. Lorem ipsum
  2. Sit amet vultatup nonumy
  3. Duista sed diam

Duis autem vel eum iriure dolor in hendrerit in vulputate velit esse molestie consequat, vel illum dolore eu feugiat nulla facilisis at vero eros et accumsan et iusto odio dignissim qui blandit praesent luptatum zzril delenit augue duis dolore te feugait nulla facilisi. Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet dolore magna aliquam erat volutpat.

Consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores.