Parallel Function Application on a DNA Substrate
In this paper I present a new model that employs a biological (specifically DNA -based) substrate for performing computation. Specifically, I describe strategies for performing parallel function application in the DNA-computing models described by Adelman, Cai et. al., and Liu et. al. Employing...
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| Language: | en_US |
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2004
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| Online Access: | http://hdl.handle.net/1721.1/5942 |
| _version_ | 1826205104087236608 |
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| author | Blumberg, Andrew Justin |
| author_facet | Blumberg, Andrew Justin |
| author_sort | Blumberg, Andrew Justin |
| collection | MIT |
| description | In this paper I present a new model that employs a biological (specifically DNA -based) substrate for performing computation. Specifically, I describe strategies for performing parallel function application in the DNA-computing models described by Adelman, Cai et. al., and Liu et. al. Employing only DNA operations which can presently be performed, I discuss some direct algorithms for computing a variety of useful mathematical functions on DNA, culminating in an algorithm for minimizing an arbitrary continuous function. In addition, computing genetic algorithms on a DNA substrate is briefly discussed. |
| first_indexed | 2024-09-23T13:07:07Z |
| id | mit-1721.1/5942 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T13:07:07Z |
| publishDate | 2004 |
| record_format | dspace |
| spelling | mit-1721.1/59422019-04-12T08:06:27Z Parallel Function Application on a DNA Substrate Blumberg, Andrew Justin AI MIT Artificial Intelligence DNA Computing Parallel Architecture In this paper I present a new model that employs a biological (specifically DNA -based) substrate for performing computation. Specifically, I describe strategies for performing parallel function application in the DNA-computing models described by Adelman, Cai et. al., and Liu et. al. Employing only DNA operations which can presently be performed, I discuss some direct algorithms for computing a variety of useful mathematical functions on DNA, culminating in an algorithm for minimizing an arbitrary continuous function. In addition, computing genetic algorithms on a DNA substrate is briefly discussed. 2004-10-04T14:15:46Z 2004-10-04T14:15:46Z 1996-12-01 AIM-1588 http://hdl.handle.net/1721.1/5942 en_US AIM-1588 14 p. 265794 bytes 210981 bytes application/postscript application/pdf application/postscript application/pdf |
| spellingShingle | AI MIT Artificial Intelligence DNA Computing Parallel Architecture Blumberg, Andrew Justin Parallel Function Application on a DNA Substrate |
| title | Parallel Function Application on a DNA Substrate |
| title_full | Parallel Function Application on a DNA Substrate |
| title_fullStr | Parallel Function Application on a DNA Substrate |
| title_full_unstemmed | Parallel Function Application on a DNA Substrate |
| title_short | Parallel Function Application on a DNA Substrate |
| title_sort | parallel function application on a dna substrate |
| topic | AI MIT Artificial Intelligence DNA Computing Parallel Architecture |
| url | http://hdl.handle.net/1721.1/5942 |
| work_keys_str_mv | AT blumbergandrewjustin parallelfunctionapplicationonadnasubstrate |