Treffer: The art of molecular computing: Whence and whither.
Title:
The art of molecular computing: Whence and whither.
Authors:
Gangadharan S; Bhupat and Jyoti Mehta School of Biosciences, Department of Biotechnology, Indian Institute of Technology Madras, Chennai, India.; Initiative for Biological Systems Engineering, Indian Institute of Technology Madras, Chennai, India., Raman K; Bhupat and Jyoti Mehta School of Biosciences, Department of Biotechnology, Indian Institute of Technology Madras, Chennai, India.; Initiative for Biological Systems Engineering, Indian Institute of Technology Madras, Chennai, India.; Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI), Indian Institute of Technology Madras, Chennai, India.
Source:
BioEssays : news and reviews in molecular, cellular and developmental biology [Bioessays] 2021 Aug; Vol. 43 (8), pp. e2100051. Date of Electronic Publication: 2021 Jun 08.
Publication Type:
Journal Article; Review; Video-Audio Media
Language:
English
Journal Info:
Publisher: Wiley Country of Publication: United States NLM ID: 8510851 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1521-1878 (Electronic) Linking ISSN: 02659247 NLM ISO Abbreviation: Bioessays Subsets: MEDLINE
Imprint Name(s):
Publication: <2005->: Hoboken, N.J. : Wiley
Original Publication: Cambridge, UK : Published for the ICSU Press by Cambridge University Press, c1984-
Original Publication: Cambridge, UK : Published for the ICSU Press by Cambridge University Press, c1984-
MeSH Terms:
References:
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Tai, Y. - S., Xiong, M., Jambunathan, P., Wang, J., Wang, J., Stapleton, C., & Zhang, K. (2016). Engineering nonphosphorylative metabolism to generate lignocellulose-derived products. Nature Chemical Biology, 12, 247-253.
Raman, R., & Bashir, R. (2017). Biomimicry, biofabrication, and biohybrid systems: The emergence and evolution of biological design. Advance Healthcare Material, 6, 1700496.
Mukai, T., Lajoie, M. J., Englert, M., & Söll, D. (2017). Rewriting the genetic code. Annual Review of Microbiology, 71, 557-577.
Forster, A. C., & Church, G. M. (2006). Towards synthesis of a minimal cell. Molecular Systems Biology, 2, 45.
Gracindo, A., Cesar, M. B., Freire, P. J. C., da Costa, A. F. M., Lins, M. R. C. R., Correa, G. G., Cerri, M. O., 2019. Engineering Microbial Living Therapeutics: The Synthetic Biology Toolbox. Trends in Biotechnology 37, 100.
Church, G. M., Gao, Y., & Kosuri, S. (2012). Next-generation digital information storage in DNA. Science, 337, 1628-1628.
Adleman, L. M. (1994). Molecular computation of solutions to combinatorial problems. Science, 266, 1021-1024.
von Neumann, J. (1956). Probabilistic logics and the synthesis of reliable organisms from unreliable components. In: Shannon, C. E., McCarthy, J. (ed.) Automata Studies. (AM-34). Princeton University Press. pp. 43-98.
McCulloch, W. S. (1960). The reliability of biological systems. In Self Organizing Systems. Pergamon., 264-79.
Ritchey, T. (2018). General morphological analysis as a basic scientific modelling method. Technology Forecasting and Social Change, 126, 81-91.
Faulhammer, D., Cukras, A. R., Lipton, R. J., & Landweber, L. R. (2000). Molecular computation: RNA solutions to chess problems. Proceedings of the National Academy of Sciences., 97, 1385-1389.
Nakagaki, T., Yamada, H., & Tóth, Á. (2000). Maze-solving by an amoeboid organism. Nature, 407, 470-470.
Liu, Q., Wang, L., Frutos, A. G., Condon, A. E., Corn, R. M., & Smith, L. M. (2000). DNA computing on surfaces. Nature, 403, 175-179.
Sakamoto, K. (2000). Molecular computation by DNA hairpin formation. Science, 288, 1223-1226.
Braich, R. S., Chelyapov, N., Johnson, C., Rothemund, P. W. K., & Adleman, L. (2002). Solution of a 20-variable 3-SAT problem on a DNA computer. Science, 296, 499-502.
Roweis, S., Winfree, E., Burgoyne, R., Chelyapov, N. V., Goodman, M. F., Rothemund, P. W., & Adleman, L. M. (1998). A sticker-based model for DNA computation. Journal of Computational Biology Journal of Computational Molecular Cell Biology, 5, 615-629.
Yurke, B., Turberfield, A. J., Mills, A. P., Simmel, F. C., & Neumann, J. L. (2000). A DNA-fuelled molecular machine made of DNA. Nature, 406, 605-608.
Seelig, G., Soloveichik, D., Zhang, D. Y., & Winfree, E. (2006). Enzyme-free nucleic acid logic circuits. Science, 314, 1585-1588.
Stojanovic, M. N., Mitchell, T. E., & Stefanovic, D. (2002). Deoxyribozyme-based logic gates. Journal of the American Chemical Society, 124, 3555-3561.
Stojanovic, M. N., & Stefanovic, D. (2003). A deoxyribozyme-based molecular automaton. Nature Biotechnology, 21, 1069-1074.
Hug, H., & Schuler, R. (2001). Strategies for the development of a peptide computer. Bioinformatics Oxford Academic. Bioinformatics, 17, 364-8.
Balan, M. S., Krithivasan, K., & Sivasubramanyam, Y. (2002). Peptide computing - universality and complexity. In: Jonoska, N., Seeman, NC. (ed.) DNA Computing. Berlin Heidelberg: Springer. pp. 290-9.
Unger, R., & Moult, J. (2006). Towards computing with proteins. Proteins, 63, 53-64.
Ramakrishnan, N., Bhalla, U. S., & Tyson, J. J. (2009). Computing with proteins. Computer, 42, 47-56.
Tsuda, S., Aono, M., & Gunji, Y. -P. (2004). Robust and emergent Physarum logical-computing. Bio Systems, 73, 45-55.
Jones, J., & Adamatzky, A. (2010). Towards Physarum binary adders. Bio Systems, 101, 51-58.
Tsuda, S., Zauner, K. - P., & Gunji, Y. - P. (2007). Robot control with biological cells. Bio Systems, 87, 215-223.
Aono, M., & Hara, M. (2008). Spontaneous deadlock breaking on amoeba-based neurocomputer. Bio Systems, 91, 83-93.
Qian, L., & Winfree, E. (2011). A simple DNA gate motif for synthesizing large-scale circuits. Journal of the Royal Society, Interface, 8, 1281-1297.
Qian, L., & Winfree, E. (2011). Scaling up digital circuit computation with DNA strand displacement cascades. Science, 332, 1196-1201.
Qian, L., Winfree, E., & Bruck, J. (2011). Neural network computation with DNA strand displacement cascades. Nature, 475, 368-372.
Little, W. A. (1974). The existence of persistent states in the brain. Mathematical Biosciences, 19, 101-120.
Cherry, K. M., & Qian, L. (2018). Scaling up molecular pattern recognition with DNA-based winner-take-all neural networks. Nature, 559, 370-376.
Song, T., Eshra, A., Shah, S., Bui, H., Fu, D., Yang, M., Mokhtar, R., & Reif, J. (2019). Fast and compact DNA logic circuits based on single-stranded gates using strand-displacing polymerase. Nature Nanotechnology, 14, 1075-1081.
Soloveichik, D., Seelig, G., & Winfree, E. (2010). DNA as a universal substrate for chemical kinetics. Proceedings of the National Academy of Sciences, 107, 5393-5398.
Chen, Y. - J., Dalchau, N., Srinivas, N., Phillips, A., Cardelli, L., Soloveichik, D., & Seelig, G. (2013). Programmable chemical controllers made from DNA. Nature Nanotechnology, 8, 755-762.
Shah, S., Song, T., Song, X., Yang, M. , & Reif, J. (2019). Implementing arbitrary CRNs using strand displacing polymerase. In. In: Thachuk, C., & Liu, Y. (ed.) DNA computing and molecular programming. Springer International Publishing. pp. 21-36.
Shah, S., Wee, J., Song, T., Ceze, L., Strauss, K., Chen, Y. - J., & Reif, J. (2020). Using strand displacing polymerase to program chemical reaction networks. Journal of the American Chemical Society, 142, 9587-93.
Seeman, N. C. (1982). Nucleic acid junctions and lattices. Journal of Theoretical Biology, 99, 237-247.
Lin, C., Liu, Y., Rinker, S., & Yan, H. (2006). DNA tile based self-assembly: Building complex nanoarchitectures. Chemphyschem, 7, 1641-1647.
Woods, D., Doty, D., Myhrvold, C., Hui, J., Zhou, F., Yin, P., & Winfree, E. (2019). Diverse and robust molecular algorithms using reprogrammable DNA self-assembly. Nature, 567, 366-372.
Jiang, Q., Song, C., Nangreave, J., Liu, X., Lin, L., Qiu, D., Wang, Z. G., Zou, G., Liang, X., Yan, H., & Ding, B. (2012). DNA origami as a carrier for circumvention of drug resistance. Journal of the American Chemical Society, 134, 13396-13403.
Amir, Y., Ben-Ishay, E., Levner, D., Ittah, S., Abu-Horowitz, A., & Bachelet, I. (2014). Universal computing by DNA origami robots in a living animal. Nature Nanotechnology, 9, 353-357.
Hemphill, J., & Deiters, A. (2013). DNA computation in mammalian cells: Microrna logic operations. Journal of the American Chemical Society, 135, 10512-10518.
Izatt, G., Wittman, S., Srinivas, N., Woods, D., Winfree, E., Qian, L., A cargo-sorting DNA robot Science 2017, 357, eaan6558.
Sheth, R. U., & Wang, H. H. (2018). DNA-based memory devices for recording cellular events. Nature Reviews Genetics, 19, 718-732.
Li, J., Green, A. A., Yan, H., & Fan, C. (2017). Engineering nucleic acid structures for programmable molecular circuitry and intracellular biocomputation. Nature Chemistry, 9, 1056-1067.
Mamet, N., Harari, G., Zamir, A., & Bachelet, I. (2019). Simulating the Monty Hall problem in a DNA sequencing machine. Computational Biology and Chemistry, 83, 107122.
Beaver, D. (1995). Computing with DNA. Journal of Computational Biology, 2, 1-7.
Ning, K. (2012). A Pseudo DNA cryptography method. Computers and Electrical Engineering, 38, 1240-1248.
Zhang, Y., Wang, F., Chao, J., Xie, M., Liu, H., Pan, M., Kopperger, E., Liu, X., Li, Q., Shi, J., Wang, L., Hu, J., Wang, L., Simmel, F. C., & Fan, C. (2019). DNA origami cryptography for secure communication. Nature Communications, 10, 5469.
Kelwick, R., Bowater, L., Yeoman, K. H., & Bowater, R. P. (2015). Promoting microbiology education through the iGEM synthetic biology competition. Fems Microbiology Letters, 362, fnv129.
Davis, J. (1996). Microvenus. Art Journal, 55, 70-74.
Church, G. M., & Regis, E. (2014). Regenesis: How synthetic biology will reinvent nature and ourselves. Hachette UK.
Goldman, N., Bertone, P., Chen, S., Dessimoz, C., LeProust, E. M., Sipos, B., & Birney, E. (2013). Towards practical, high-capacity, low-maintenance information storage in synthesized DNA. Nature, 494, 77-80.
Zhirnov, V., Zadegan, R. M., Sandhu, G. S., Church, G. M., & Hughes, W. L. (2016). Nucleic acid memory. Nature Materials, 15, 366-370.
Grass, R. N., Heckel, R., Puddu, M., Paunescu, D., & Stark, W. J. (2015). Robust chemical preservation of digital information on DNA in silica with error-correcting codes. Angewandte Chemie, International Edition, 54, 2552-2555.
Shipman, S. L., Nivala, J., Macklis, J. D., & Church, G. M. (2016). Molecular recordings by directed CRISPR spacer acquisition. Science, 353, aaf1175.
Ceze, L., Nivala, J., & Strauss, K. (2019). Molecular digital data storage using DNA. Nature Reviews Genetics, 20, 456-466.
De Silva, P. Y., & Ganegoda, G. U. (2016). New trends of digital data storage in DNA. BioMed Research International, 2016, 1-14.
Tabatabaei Yazdi, S. M. H., Yuan, Y., Ma, J., Zhao, H., & Milenkovic, O. (2015). A rewritable, random-access DNA-based storage system. Scientific Reports, 5, 14138.
Organick, L., Ang, S. D., Chen, Y. - J., Lopez, R., Yekhanin, S., Makarychev, K., Racz, M. Z., Kamath, G., Gopalan, P., Nguyen, B., Takahashi, C. N., Newman, S., Parker, H. - Y., Rashtchian, C., Stewart, K., Gupta, G., Carlson, R., Mulligan, J., Carmean, D. … Strauss, K. (2018). Random access in large-scale DNA data storage. Nature Biotechnology, 36, 242-248.
Takahashi, C. N., Nguyen, B. H., Strauss, K., & Ceze, L. (2019). Demonstration of end-to-end automation of DNA data storage. Scientific Reports, 9, 4998.
Organick, L., Chen, Y. -J., Dumas Ang, S., Lopez, R., Liu, X., Strauss, K., & Ceze, L. (2020). Probing the physical limits of reliable DNA data retrieval. Nature Communications, 11, 616.
Li, Y., Sun, S., Fan, L., Hu, S., Huang, Y., Zhang, K., Nie, Z., & Yao, S. (2017). Peptide logic circuits based on chemoenzymatic ligation for programmable cell apoptosis. Angewandte Chemie, International Edition, 56, 14888-14892.
Ho, T. Y. H., Shao, A., Lu, Z., Savilahti, H., Menolascina, F., Wang, L., Dalchau, N., & Wang, B. (2021). A systematic approach to inserting split inteins for Boolean logic gate engineering and basal activity reduction. Nature Communications, 12, 2200.
Balan, M. S., & Krithivasan, K. (2004). Parallel computation of simple arithmetic using peptide-antibody interactions. Bio Systems, 76, 303-307.
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Jacob, F., Perrin, D., Sánchez, C., & Monod, J. (2005). L'opéron: Groupe de gènes à expression coordonnée par un opérateur [C. R. Acad. Sci. Paris, 250 (1960) 1727-1729]. Comptes Rendus Biologies, 328, 514-520.
Tai, Y. - S., Xiong, M., Jambunathan, P., Wang, J., Wang, J., Stapleton, C., & Zhang, K. (2016). Engineering nonphosphorylative metabolism to generate lignocellulose-derived products. Nature Chemical Biology, 12, 247-253.
Raman, R., & Bashir, R. (2017). Biomimicry, biofabrication, and biohybrid systems: The emergence and evolution of biological design. Advance Healthcare Material, 6, 1700496.
Mukai, T., Lajoie, M. J., Englert, M., & Söll, D. (2017). Rewriting the genetic code. Annual Review of Microbiology, 71, 557-577.
Forster, A. C., & Church, G. M. (2006). Towards synthesis of a minimal cell. Molecular Systems Biology, 2, 45.
Gracindo, A., Cesar, M. B., Freire, P. J. C., da Costa, A. F. M., Lins, M. R. C. R., Correa, G. G., Cerri, M. O., 2019. Engineering Microbial Living Therapeutics: The Synthetic Biology Toolbox. Trends in Biotechnology 37, 100.
Church, G. M., Gao, Y., & Kosuri, S. (2012). Next-generation digital information storage in DNA. Science, 337, 1628-1628.
Adleman, L. M. (1994). Molecular computation of solutions to combinatorial problems. Science, 266, 1021-1024.
von Neumann, J. (1956). Probabilistic logics and the synthesis of reliable organisms from unreliable components. In: Shannon, C. E., McCarthy, J. (ed.) Automata Studies. (AM-34). Princeton University Press. pp. 43-98.
McCulloch, W. S. (1960). The reliability of biological systems. In Self Organizing Systems. Pergamon., 264-79.
Ritchey, T. (2018). General morphological analysis as a basic scientific modelling method. Technology Forecasting and Social Change, 126, 81-91.
Faulhammer, D., Cukras, A. R., Lipton, R. J., & Landweber, L. R. (2000). Molecular computation: RNA solutions to chess problems. Proceedings of the National Academy of Sciences., 97, 1385-1389.
Nakagaki, T., Yamada, H., & Tóth, Á. (2000). Maze-solving by an amoeboid organism. Nature, 407, 470-470.
Liu, Q., Wang, L., Frutos, A. G., Condon, A. E., Corn, R. M., & Smith, L. M. (2000). DNA computing on surfaces. Nature, 403, 175-179.
Sakamoto, K. (2000). Molecular computation by DNA hairpin formation. Science, 288, 1223-1226.
Braich, R. S., Chelyapov, N., Johnson, C., Rothemund, P. W. K., & Adleman, L. (2002). Solution of a 20-variable 3-SAT problem on a DNA computer. Science, 296, 499-502.
Roweis, S., Winfree, E., Burgoyne, R., Chelyapov, N. V., Goodman, M. F., Rothemund, P. W., & Adleman, L. M. (1998). A sticker-based model for DNA computation. Journal of Computational Biology Journal of Computational Molecular Cell Biology, 5, 615-629.
Yurke, B., Turberfield, A. J., Mills, A. P., Simmel, F. C., & Neumann, J. L. (2000). A DNA-fuelled molecular machine made of DNA. Nature, 406, 605-608.
Seelig, G., Soloveichik, D., Zhang, D. Y., & Winfree, E. (2006). Enzyme-free nucleic acid logic circuits. Science, 314, 1585-1588.
Stojanovic, M. N., Mitchell, T. E., & Stefanovic, D. (2002). Deoxyribozyme-based logic gates. Journal of the American Chemical Society, 124, 3555-3561.
Stojanovic, M. N., & Stefanovic, D. (2003). A deoxyribozyme-based molecular automaton. Nature Biotechnology, 21, 1069-1074.
Hug, H., & Schuler, R. (2001). Strategies for the development of a peptide computer. Bioinformatics Oxford Academic. Bioinformatics, 17, 364-8.
Balan, M. S., Krithivasan, K., & Sivasubramanyam, Y. (2002). Peptide computing - universality and complexity. In: Jonoska, N., Seeman, NC. (ed.) DNA Computing. Berlin Heidelberg: Springer. pp. 290-9.
Unger, R., & Moult, J. (2006). Towards computing with proteins. Proteins, 63, 53-64.
Ramakrishnan, N., Bhalla, U. S., & Tyson, J. J. (2009). Computing with proteins. Computer, 42, 47-56.
Tsuda, S., Aono, M., & Gunji, Y. -P. (2004). Robust and emergent Physarum logical-computing. Bio Systems, 73, 45-55.
Jones, J., & Adamatzky, A. (2010). Towards Physarum binary adders. Bio Systems, 101, 51-58.
Tsuda, S., Zauner, K. - P., & Gunji, Y. - P. (2007). Robot control with biological cells. Bio Systems, 87, 215-223.
Aono, M., & Hara, M. (2008). Spontaneous deadlock breaking on amoeba-based neurocomputer. Bio Systems, 91, 83-93.
Qian, L., & Winfree, E. (2011). A simple DNA gate motif for synthesizing large-scale circuits. Journal of the Royal Society, Interface, 8, 1281-1297.
Qian, L., & Winfree, E. (2011). Scaling up digital circuit computation with DNA strand displacement cascades. Science, 332, 1196-1201.
Qian, L., Winfree, E., & Bruck, J. (2011). Neural network computation with DNA strand displacement cascades. Nature, 475, 368-372.
Little, W. A. (1974). The existence of persistent states in the brain. Mathematical Biosciences, 19, 101-120.
Cherry, K. M., & Qian, L. (2018). Scaling up molecular pattern recognition with DNA-based winner-take-all neural networks. Nature, 559, 370-376.
Song, T., Eshra, A., Shah, S., Bui, H., Fu, D., Yang, M., Mokhtar, R., & Reif, J. (2019). Fast and compact DNA logic circuits based on single-stranded gates using strand-displacing polymerase. Nature Nanotechnology, 14, 1075-1081.
Soloveichik, D., Seelig, G., & Winfree, E. (2010). DNA as a universal substrate for chemical kinetics. Proceedings of the National Academy of Sciences, 107, 5393-5398.
Chen, Y. - J., Dalchau, N., Srinivas, N., Phillips, A., Cardelli, L., Soloveichik, D., & Seelig, G. (2013). Programmable chemical controllers made from DNA. Nature Nanotechnology, 8, 755-762.
Shah, S., Song, T., Song, X., Yang, M. , & Reif, J. (2019). Implementing arbitrary CRNs using strand displacing polymerase. In. In: Thachuk, C., & Liu, Y. (ed.) DNA computing and molecular programming. Springer International Publishing. pp. 21-36.
Shah, S., Wee, J., Song, T., Ceze, L., Strauss, K., Chen, Y. - J., & Reif, J. (2020). Using strand displacing polymerase to program chemical reaction networks. Journal of the American Chemical Society, 142, 9587-93.
Seeman, N. C. (1982). Nucleic acid junctions and lattices. Journal of Theoretical Biology, 99, 237-247.
Lin, C., Liu, Y., Rinker, S., & Yan, H. (2006). DNA tile based self-assembly: Building complex nanoarchitectures. Chemphyschem, 7, 1641-1647.
Woods, D., Doty, D., Myhrvold, C., Hui, J., Zhou, F., Yin, P., & Winfree, E. (2019). Diverse and robust molecular algorithms using reprogrammable DNA self-assembly. Nature, 567, 366-372.
Jiang, Q., Song, C., Nangreave, J., Liu, X., Lin, L., Qiu, D., Wang, Z. G., Zou, G., Liang, X., Yan, H., & Ding, B. (2012). DNA origami as a carrier for circumvention of drug resistance. Journal of the American Chemical Society, 134, 13396-13403.
Amir, Y., Ben-Ishay, E., Levner, D., Ittah, S., Abu-Horowitz, A., & Bachelet, I. (2014). Universal computing by DNA origami robots in a living animal. Nature Nanotechnology, 9, 353-357.
Hemphill, J., & Deiters, A. (2013). DNA computation in mammalian cells: Microrna logic operations. Journal of the American Chemical Society, 135, 10512-10518.
Izatt, G., Wittman, S., Srinivas, N., Woods, D., Winfree, E., Qian, L., A cargo-sorting DNA robot Science 2017, 357, eaan6558.
Sheth, R. U., & Wang, H. H. (2018). DNA-based memory devices for recording cellular events. Nature Reviews Genetics, 19, 718-732.
Li, J., Green, A. A., Yan, H., & Fan, C. (2017). Engineering nucleic acid structures for programmable molecular circuitry and intracellular biocomputation. Nature Chemistry, 9, 1056-1067.
Mamet, N., Harari, G., Zamir, A., & Bachelet, I. (2019). Simulating the Monty Hall problem in a DNA sequencing machine. Computational Biology and Chemistry, 83, 107122.
Beaver, D. (1995). Computing with DNA. Journal of Computational Biology, 2, 1-7.
Ning, K. (2012). A Pseudo DNA cryptography method. Computers and Electrical Engineering, 38, 1240-1248.
Zhang, Y., Wang, F., Chao, J., Xie, M., Liu, H., Pan, M., Kopperger, E., Liu, X., Li, Q., Shi, J., Wang, L., Hu, J., Wang, L., Simmel, F. C., & Fan, C. (2019). DNA origami cryptography for secure communication. Nature Communications, 10, 5469.
Kelwick, R., Bowater, L., Yeoman, K. H., & Bowater, R. P. (2015). Promoting microbiology education through the iGEM synthetic biology competition. Fems Microbiology Letters, 362, fnv129.
Davis, J. (1996). Microvenus. Art Journal, 55, 70-74.
Church, G. M., & Regis, E. (2014). Regenesis: How synthetic biology will reinvent nature and ourselves. Hachette UK.
Goldman, N., Bertone, P., Chen, S., Dessimoz, C., LeProust, E. M., Sipos, B., & Birney, E. (2013). Towards practical, high-capacity, low-maintenance information storage in synthesized DNA. Nature, 494, 77-80.
Zhirnov, V., Zadegan, R. M., Sandhu, G. S., Church, G. M., & Hughes, W. L. (2016). Nucleic acid memory. Nature Materials, 15, 366-370.
Grass, R. N., Heckel, R., Puddu, M., Paunescu, D., & Stark, W. J. (2015). Robust chemical preservation of digital information on DNA in silica with error-correcting codes. Angewandte Chemie, International Edition, 54, 2552-2555.
Shipman, S. L., Nivala, J., Macklis, J. D., & Church, G. M. (2016). Molecular recordings by directed CRISPR spacer acquisition. Science, 353, aaf1175.
Ceze, L., Nivala, J., & Strauss, K. (2019). Molecular digital data storage using DNA. Nature Reviews Genetics, 20, 456-466.
De Silva, P. Y., & Ganegoda, G. U. (2016). New trends of digital data storage in DNA. BioMed Research International, 2016, 1-14.
Tabatabaei Yazdi, S. M. H., Yuan, Y., Ma, J., Zhao, H., & Milenkovic, O. (2015). A rewritable, random-access DNA-based storage system. Scientific Reports, 5, 14138.
Organick, L., Ang, S. D., Chen, Y. - J., Lopez, R., Yekhanin, S., Makarychev, K., Racz, M. Z., Kamath, G., Gopalan, P., Nguyen, B., Takahashi, C. N., Newman, S., Parker, H. - Y., Rashtchian, C., Stewart, K., Gupta, G., Carlson, R., Mulligan, J., Carmean, D. … Strauss, K. (2018). Random access in large-scale DNA data storage. Nature Biotechnology, 36, 242-248.
Takahashi, C. N., Nguyen, B. H., Strauss, K., & Ceze, L. (2019). Demonstration of end-to-end automation of DNA data storage. Scientific Reports, 9, 4998.
Organick, L., Chen, Y. -J., Dumas Ang, S., Lopez, R., Liu, X., Strauss, K., & Ceze, L. (2020). Probing the physical limits of reliable DNA data retrieval. Nature Communications, 11, 616.
Li, Y., Sun, S., Fan, L., Hu, S., Huang, Y., Zhang, K., Nie, Z., & Yao, S. (2017). Peptide logic circuits based on chemoenzymatic ligation for programmable cell apoptosis. Angewandte Chemie, International Edition, 56, 14888-14892.
Ho, T. Y. H., Shao, A., Lu, Z., Savilahti, H., Menolascina, F., Wang, L., Dalchau, N., & Wang, B. (2021). A systematic approach to inserting split inteins for Boolean logic gate engineering and basal activity reduction. Nature Communications, 12, 2200.
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Contributed Indexing:
Keywords: DNA computing; DNA data storage; logic gates; molecular machines; unconventional computing
Substance Nomenclature:
9007-49-2 (DNA)
Entry Date(s):
Date Created: 20210608 Date Completed: 20211028 Latest Revision: 20220531
Update Code:
20250114
DOI:
10.1002/bies.202100051
PMID:
34101866
Database:
MEDLINE
Weitere Informationen
An astonishingly diverse biomolecular circuitry orchestrates the functioning machinery underlying every living cell. These biomolecules and their circuits have been engineered not only for various industrial applications but also to perform other atypical functions that they were not evolved for-including computation. Various kinds of computational challenges, such as solving NP-complete problems with many variables, logical computation, neural network operations, and cryptography, have all been attempted through this unconventional computing paradigm. In this review, we highlight key experiments across three different ''eras'' of molecular computation, beginning with molecular solutions, transitioning to logic circuits and ultimately, more complex molecular networks. We also discuss a variety of applications of molecular computation, from solving NP-hard problems to self-assembled nanostructures for delivering molecules, and provide a glimpse into the exciting potential that molecular computing holds for the future. Also see the video abstract here: https://youtu.be/9Mw0K0vCSQw.
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