Abstract
The relatedness between knowledge components within the science domain is widely discussed in the economic, innovation, and management literature. The same is true for the technology domain. Yet, the relatedness between knowledge components across these knowledge domains has received considerably less attention. This chapter aims to introduce the concept of knowledge relatedness between science and technology (S&T), which have been disentangled as two distinct corpora. We approach S&T relatedness from two perspectives: content relatedness (with four indicators: similarity, complementarity, commonality, difference) and temporal relatedness. We then test our ideas with novel empirical material from the field of DNA nanoscience and DNA nanotechnology. We find that the relatedness between S&T scores relatively low, which may explain the relative lack of commercial activity in this field. In light of their indirect complementarity, we recommend that funding “bridging areas” could lead to simultaneous progress in S&T.
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Notes
- 1.
- 2.
We later refer to these as PPPs.
- 3.
We later refer to it as NPL.
- 4.
The main path approach is a network analysis tool introduced in the late 1980s to investigate networks of scientific publications, and later to study patent networks (see Verspagen, 2007; Bekkers & Martinelli, 2012). The top main path is considered as representing the most important developments in citation networks.
- 5.
In a similar vein, Heinisch et al. (2016) used co-location as a proxy for direct knowledge interaction.
- 6.
Both directly and indirectly.
- 7.
Note that while we use the term “academic publications,” such publications can also be authored by people working for firms. Likewise, university staff can also apply for patents.
- 8.
They are “term groups,” which consist of synonyms, abbreviations…which have the same meaning.
- 9.
We used two levels of analysis: domain level, and term level.
- 10.
This may due to the fact there is no fixed perfect definition for a new field.
- 11.
Precision can be estimated by taking a random sample of the set, and manually investigating whether all the records indeed belong to the sought field. Recall can be estimated by independently creating a set of records that are known to belong to the sought set (e.g., by asking an independent expert in the field, or selecting the relevant patents or publications of key contributors) and then testing whether these records are present in the set.
- 12.
We found that, in our context, four was the number of concepts allowing us to reach the best balance between recall and precision. With three concepts, the level of precision reduced significantly. With five concepts, the concepts started to lose their initial independence, and the level of recall dropped.
- 13.
Information sources include materials and notes taken at technical conferences on DNA-Nano, communication with experts by email and Skype, and publications and news items in the field of DNA-Nano.
- 14.
Sungi Kim, PhD candidate at Seoul National University, validated the queries for collecting publications. Jürgen Schmied, CEO of Gattaquant, a company working in the field of DNA Nanotechnology, validated the queries for collecting patents.
- 15.
We improved recall by checking whether the authors and inventors whom we know are present in our search results. If not, we included more keywords from their publications/patents. We improved precision by sampling 20 records each time and checking if any record is irrelevant. Then we identified the keywords that distinguish DNA-Nano from other fields in that record, and put them in the exclusion terms.
- 16.
And even those with high term frequency-inverse document frequency (tf*idf).
- 17.
For instance, “this study,” “this invention.”
- 18.
We ended up with 109 cross-domain term groups, which have been harmonized from 400 technical terms extracted with highest scores by the automatic Term Recognition algorithm.
- 19.
We used Higuchi Koichi’s KH coder text-mining software (Version 3a12d).
- 20.
A sub-domain unit of analysis.
- 21.
We used Stephan Evert’s R package “corpora” for this specific Chi-square test.
- 22.
We explained how we selected 109 term groups in Sect. 3.2. For the actual analysis of S&T relatedness, we called them “terms” for convenience.
- 23.
This first step resulted in 538 pairs in Science and 391 pairs in Technology.
- 24.
This second step resulted in 133 pairs of direct complementarity and 10,525 pairs of indirect complementarity.
- 25.
In earlier ages, however, the temporal relatedness between S&T could happen in 2000 years (Johns, 2020).
- 26.
These robustness checks are available upon demand from the authors.
- 27.
This does not happen with knowledge areas that are neither similar nor complementary.
- 28.
We did so at the third workshop on Functional DNA Nanotechnology (6–8 June 2018, Rome, Italy).
- 29.
We explained the concepts of direct and indirect complementarity, and gave them the list of 133 pairs of terms. Some experts reacted right away, others responded later by email.
- 30.
For reasons indicated in Sect. 4.2, we did not measure indirect complementarity over the different subperiods.
- 31.
It is harder practically to achieve precision in retrieving patents rather than retrieving publications. Therefore, we decided to adjust terminologies in this DNA concept group into more specific terms, which include DNA.
References
Arora, S. K., Porter, A. L., Youtie, J., & Shapira, P. (2013). Capturing new developments in an emerging technology: An updated search strategy for identifying nanotechnology research outputs. Scientometrics, 95, 351–370.
Arthur, W. B. (2009). The nature of technology: What it is and how it evolves. Free Press.
Bekkers, R., & Martinelli, A. (2012). Knowledge positions in high-tech markets: Trajectories, standards, strategies and true innovators. Technological Forecasting and Social Change, 79, 1192–1216.
Benson, C. L., & Magee, C. L. (2013). A hybrid keyword and patent class methodology for selecting relevant sets of patents for a technological field. Scientometrics, 96, 69–82.
Benson, C. L., & Magee, C. L. (2015). Technology structural implications from the extension of a patent search method. Scientometrics, 102, 1965–1985.
Boschma, R., & Frenken, K. (2009). Technological relatedness and regional branching. Retrieved from http://econ.geo.uu.nl/peeg/peeg.html
Boschma, R., Heimeriks, G., & Balland, P. (2014). Scientific knowledge dynamics and relatedness in biotech cities. Research Policy, 43, 107–114.
Boyack, K. W., & Klavans, R. (2008). Measuring science–technology interaction using rare inventor–author names. Journal of Informetrics, 2, 173–182.
Breschi, S., & Catalini, C. (2010). Tracing the links between S&T: An exploratory analysis of scientists and inventors networks. Research Policy, 39, 14–26.
Chang, Y. W., Yang, H. W., & Huang, M. W. (2017). Interaction between S&T in the field of fuel cells based on patent paper analysis. Electronic Library, 35, 152–166.
Daim, T., Monalisa, M., Dash, P., & Brown, N. (2007). Time lag assessment between research funding and output in emerging technologies. Foresight, 9(4), 33–44.
Dosi, G. (1982). Technological paradigms and technological trajectories. Research Policy, 22, 102–103.
Douglas, K. (2016). DNA nanoscience: From prebiotic origins to emerging nanotechnology. CRC Press.
Drexler, K. E. (2013). Radical abundance: How a revolution in nanotechnology will change civilization. Public Affairs.
Dunn, K. E. (2020). The business of DNA nanotechnology: Commercialization of origami and other technologies. Molecules, 25, 377.
Evert, S. (2005). The statistics of word cooccurrences word pairs and collocations. Dissertation, Institut für maschinelle Sprachverarbeitung, Universität Stuttgart. Retrieved from http://elib.uni-stuttgart.de/bitstream/11682/2573/1/Evert2005phd.pdf
Finardi, U. (2011). Time relations between scientific production and patenting of knowledge: The case of nanotechnologies. Scientometrics, 89, 37–50.
Heinisch, D., Nomaler, Ö., Buenstorf, G., Frenken, K., & Lintsen, H. (2016). Same place, same knowledge–same people? The geography of non-patent citations in Dutch polymer patents. Economics of Innovation and New Technology, 25, 553–572.
Huang, Y., Schuehle, J., Porter, A. L., & Youtie, J. (2015). A systematic method to create search strategies for emerging technologies based on the Web of Science: Illustrated for ‘Big Data’. Scientometrics, 105, 2005–2022.
Johns, C. M. (2020). The industrial revolution-lost in antiquity-found in the renaissance. Pumbo.nl.
Kilgarriff, A. (2001). Comparing corpora. International Journal of Corpus Linguistics, 6, 97–133.
Kuhn, T. S. (1970). The structure of scientific revolutions (2nd ed.). University of Chicago Press.
La, H. L., & Bekkers R. N. A. (2018, June 11–13). The relation between scientific and technological knowledge in emerging fields: Evidence from DNA nanoscience and DNA nanotechnology. Paper presented at DRUID18 conference, Copenhagen, Denmark.
Layton, E. T. (1974). Technology as knowledge. Technology and Culture, 15, 31–41.
Makri, M., Hitt, M. A., & Lane, P. J. (2010). Complementary technologies, knowledge relatedness, and invention outcomes in high technology mergers and acquisitions. Strategic Management Journal, 31, 602–628.
Meyer, M. (2000). Does science push technology? Patents citing scientific literature. Research Policy, 29, 409–434.
Mina, A., Ramlogan, R., Tampubolon, G., & Metcalfe, J. S. (2007). Mapping evolutionary trajectories: Applications to the growth and transformation of medical knowledge. Research Policy, 36, 789–806.
Murray, F. (2002). Innovation as co-evolution of scientific and technological networks: Exploring tissue engineering. Research Policy, 31, 1389–1403.
Nakagawa, H. (2000). Automatic term recognition based on statistics of compound nouns. Terminology. International Journal of Theoretical and Applied Issues in Specialized Communication, 6, 195–210.
Narin, F., Hamilton, K. S., & Olivastro, D. (1997). The increasing linkage between U.S. technology and public science. Research Policy, 26, 317–330.
Nature Research. (2018, January 1). DNA nanotechnology. Retrieved from https://www.nature.com/subjects/dna-nanotechnology
Nelson, R. R., & Winter, S. G. (1974). Neoclassical vs. evolutionary theories of economic growth: Critique and prospectus. Economic Journal, 84, 886–905.
Nomaler, O., & Verspagen, B. (2008). Knowledge flows, patent citations and the impact of science on technology. Economic Systems Research, 20(4), 339–366.
Nordmann, A. (2008). Philosophy of NanoTechnoScience. In G. Schmid, H. Krug, R. Waser, V. Vogel, H. Fuchs, M. Grätzel, K. Kalyanasundaram, & L. Chi (Eds.), Nanotechnology, Vol. 1: Principles and fundamentals (pp. 217–244). Wiley.
Patra, D. (2011). Nanotechnoscience, nanotechnology, or nanotechnoscience: Perceptions of Indian nanoresearchers. Public Understanding of Science, 22, 590–605.
Pavitt, K. (1987). The objectives of technology policy. Science and Public Policy, 14, 182–188.
Pinheiro, A. V., Han, D., Shih, W. M., & Yan, H. (2011). Challenges and opportunities for structural DNA nanotechnology. Nature Nanotechnology, 6, 763–772.
Porter, A. L., Youtie, J., Shapira, P., & Schoeneck, D. J. (2008). Refining search terms for nanotechnology. Journal of Nanoparticle Research, 10, 715–728.
Price, D. S. D. J. (1965). Is technology historically independent of science? A study in statistical historiography. Technology and Culture, 6, 553–568.
Rayson, P., & Garside, R. (2000). Comparing corpora using frequency profiling. In: Proceedings of the workshop on comparing corpora (vol. 9, pp. 1–6). Association for Computational Linguistics.
Rothemund, P. W. K. (2006). Folding DNA to create nanoscale shapes and patterns. Nature, 440, 297–302.
Suenaga, K. (2015). The emergence of technological paradigms: The evolutionary process of S&T in economic development. In A. Pyka & J. Foster (Eds.), The evolution of economic and innovation systems. Economic complexity and evolution (pp. 211–227). Springer.
Tripodi, G., Chiaromonte, F., & Lillo, F. (2020). Knowledge and social relatedness shape research portfolio diversification. Scientific Reports, 10(1) Nature.
US National Nanotechnology Initiative. (2000). What is nanotechnology? Retrieved from https://www.nano.gov/nanotech-101/what/definition
Verbeek, A., Debackere, K., Luwel, M., Andries, P., Zimmermann, E., & Deleus, F. (2002). Linking science to technology: Using bibliographic references in patents to build linkage schemes. Scientometrics, 54, 399–420.
Verspagen, B. (2007). Mapping technological trajectories as patent citation networks: A study on the history of fuel cell research. Advances in Complex Systems, 10(1), 93–115.
Wang, L., & Li, Z. (2018). Knowledge transfer from science to technology—the case of nano medical device technologies. Frontiers in Research Metrics and Analytics, 3, 11.
Zhao, Q., & Guan, J. (2013). Love dynamics between S&T: Some evidences in nanoscience and nanotechnology. Scientometrics, 94, 113–132.
Acknowledgments
The Vietnamese Government sponsored this research in an overseas training program for Ph.D. candidates. We are indebted to Önder Nomaler and Cort MacLean Johns for their discussion and support. We acknowledge Higuchi Koichi for his technical support with the software KH Coder. We are thankful to have insights into the practical research of DNA Nanotechnology, presented and enlightened by experts at these conferences: DNA22, DNA meets Plasmonics, FDN2018. We are grateful to Nadrian Seeman for validating our results, and Jürgen Schmied and Sungi Kim for verifying our queries, Bas Rosier for sharing his insights on DNA Nanotechnology. We especially appreciate the constructive comments from discussants Virgilio Failla, Hans Christian Kongsted, the audience at the DRUID18 conference, from Piergiuseppe Morone at the ISS2018 conference, and two anonymous reviewers for this book chapter. We would also like to thank Nguyen Van Dan (Academy of Finance) for moral support.
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This study was funded by a Vietnamese Government scholarship for conducting Ph.D. studies abroad, according to Decision No. 1908, 30 May 2013, by the Ministry of Education and Training. Mrs. Hanh Luong La was the recipient of this scholarship. She also received the travel grant from the Eindhoven University of Technology to present the earlier version of the chapter at the ISS2018 conference in Seoul.
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The authors declare that they have no conflict of interest.
Annex. The Four Concepts Applied in the Concept Approach
It is worthwhile noting that some records where the concept “nanotechnology” is implicit, should be included in our datasets. Certain inventors choose not to mention nano-related terms explicitly or discuss only DNA or oligonucleotides. That might be the reason why a considerable number of patents belonging to DNA Nanotechnology is not classified under IPC-code B82 (Nanotechnology). From a conceptual point of view, DNA and nano are quite different. However, from a practical point of view, when discussing DNA or nucleotides, we should imply that the research is conducted at the nanoscale, since the dimension of a DNA strand is approximately 2.5 nm. Therefore, “DNA” and “*nucleotid*” are included in two concept areas (Nanotechnology and DNA) to avoid missing certain records that do not mention nano-related terms. Although DNA and Nanotechnology are closely related concepts, we have not grouped them because this leads to considerably more noise in the datasets selected. Thus, DNA-related terms must appear in the set under any conditions, while the presence of nano-related terms remains an option.
Annex. The Four Concepts Applied in the Concept Approach
1.1 1. Description of the Four Concepts, as Well as the Exclusion Mechanisms Used
Concept A: Nanotechnology | “Nanotechnology is science, engineering, and technology conducted at the nanoscale, which is about 1 to 100 nanometers” (definition from the US National Nanotechnology Initiative, 2000). Thus, any science or technology that works below the scale of 100 nanometers is considered “nanotechnology.” This definition is a broad one. We could therefore maximize our search by collecting synonyms referring to nanoscale or instruments used in nanotechnologies, such as specific types of microscopes (AFM, TEM, SEM) |
Concept B: Design | The word “design” has two forms, the verb and the noun. As a noun, “design” refers to an object or an entity. As a verb, it refers to a process or series of activities. Design is the construction of an object or creation of an entity. An interesting feature of the DNA origami technique is that DNA strands are programmed, synthesized, and can self-assemble themselves afterward. We found all terms related to this process and listed them under the concept “design” |
Concept C: Structure | Structure is defined by the Oxford Dictionary as “a particular arrangement of parts.” We found several synonyms of “structure” based on publications and patents in DNA-Nano by top contributors in the field such as Nadrian Seeman, Paul Rothemund, and others. We also noted specific words related to DNA structures and included them in our search |
Concept D: DNA | DNA is the abbreviation of “deoxyribonucleic acid,” a type of nucleic acid, a chemical that carries genetic information in the cells of animals and plants (Oxford Dictionary), or any living organisms, and viruses (Wikipedia). It is interesting to note that the term DNA, as used in our research, refers to artificial DNA, not its natural form. However, its synonyms and related terms are borrowed from molecular biology |
Exclusion terms in Titles (E1) | At the first level of exclusion, we excluded specific terms relating to other closely linked fields (e.g., molecular biology, genetic engineering, forensics). However, these terms could still appear in abstracts or keywords |
Exclusion terms in Titles, Abstracts, and Keywords (E2) | At the second level of exclusion, we excluded the terms that should not appear in titles, abstracts, and keywords. This strongest exclusion has improved the precision of our data |
1.2 2. Final Queries
Query for Publications
(Nanotechnology AND Design AND Structure AND DNA) NOT (E1 OR E2)
.. where
Nanotechnology = NANO* OR ‘ATOM* FORCE MICROSCOP*’ OR AFM OR TEM OR ‘TRANSMISSION ELECTRON MICROSCOP*’ OR SEM OR ‘SCANNING ELECTRON MICROSCOP*’ OR ‘FLUORESCENCE MICROSCOP*’ OR ‘CRYO-ELECTRON MICROSCOP*’ OR ‘CRYO-EM’ OR MOLECUL* OR MULTIMER$ OR MONOMER$
Design = DESIGN* OR COMPUT* OR CONJUGAT* OR FORM* OR FOLD* OR JUXTAPOS* OR PROGRAM* OR BIND* OR BOUND OR ATTACH* OR LINK* OR CONNECT* OR CONSTRUCT* OR BRANCH* OR BOND* OR FABRICAT* OR ‘SELF-ASSEMBL*’ OR ‘SELF-REPLICAT*’ OR ‘SELF-ORGANI*’ OR ‘DIRECTED-ASSEMBL*’ OR SYNTHETIC OR ARTIFICIAL OR ‘NON-NATURAL’ OR UNNATURAL OR ‘NON-GENETIC’
Structure = ‘*STRUCTURE$’ OR DOMAIN$ OR SYSTEM* OR MOTOR* OR MACHIN* OR DEVICE$ OR ARRAY$ OR POLYHEDR* OR CONJUGATE$ OR LADDER$ OR ‘*ROBOT*’ OR JUNCTION$ OR SCAFFOLD* OR TEMPLAT* OR TILE$ OR TILING$ OR LATTICE$ OR ‘STICKY END*’ OR ‘COHESIVE END*’ OR STAPL* OR ‘LOGIC GATE*’ OR CIRCUIT$ OR ORIGAMI
DNA = DNA* OR ‘*NUCLEIC ACID*’ OR ‘DOUBLE HELI*’ OR HELICES OR ‘*STRAND*’ OR ‘*NUCLEOTID*’ OR FOLDAMER$ OR APTAMER$
E1 = RIBONUCLEIC OR CELL$ OR THERAP* OR INFLAMMAT* OR RIBOSOME$ OR BODY* OR SPECIES* OR BRAIN* OR ‘MOLECULAR CLONING’ OR EVOLUTION* OR IMMUN* OR DISORDER$ OR VIRUS* OR ORGANISM$ OR ORGAN$ OR BACTERI* OR ANTIBOD* OR HUMAN* OR MAMMAL$ OR TISSUE$ OR TRANSCRIPTION OR RAT$ OR MICE OR HSP* OR P53 OR STAT3 OR ‘NON-NUCLEIC’ OR ‘DNA SEQUENCING’ OR ‘GENETIC ENGINEERING’ OR GENETICS OR SYMPTOM$
E2 = METABOL* OR GEOGRAPH* OR NUTRI* OR YEAST$ OR TREE$ OR SOIL OR FISH* OR MARINE OR INJUR* OR WOUND* OR ‘GENE EXPRESSION’ OR ‘GENETIC STRUCTURE’ OR ‘GENETICALLY MODIFIED’ OR GMO OR ‘GENETICALLY ENGINEERED’ OR ‘GENE REGULATION$’ OR ‘GENETIC ALGORITHM$’ OR ‘GENE DELIVERY’ OR ‘GENE INTERACTION$’ OR ‘GENO*’ OR ‘PHYLOGEN*’ OR TRANSGENIC OR HORMON* OR ESTROGEN OR TESTOSTERONE OR PATIENT$ OR EMBRYO* OR POLYMERASE OR VACCIN* OR ANTIBIOTIC$ OR BLOOD OR FETAL OR FETUS OR OFFSPRING$ OR BLAST OR FUNG* OR MUTAT* OR CHROMOSOME OR ‘PRO POLYPEPTIDE$’ OR HELICASE OR INFECT* OR INSECT* OR PLANT$ OR ANIMAL$ OR FORENSIC$ OR NANOPLANKTON OR NANOFAUNA OR CAS9* OR NANO2 OR NANO3
Query for Patents
(Nanotechnology AND Design AND Structure AND DNA) NOT (E1 OR E2)
.. where
Nanotechnology = NANO* OR ‘ATOM* FORCE MICROSCOP*’ OR AFM OR TEM OR ‘TRANSMISSION ELECTRON MICROSCOP*’ OR SEM OR ‘SCANNING ELECTRON MICROSCOP*’ OR ‘FLUORESCENCE MICROSCOP*’ OR ‘CRYO-ELECTRON MICROSCOP*’ OR ‘CRYO-EM’ OR MOLECUL* OR MULTIMER$ OR MONOMER$ OR ‘*NUCLEOTID*’ OR DNA
Design = CONJUGAT* OR FORM* OR FOLD* OR JUXTAPOS* OR PROGRAM* OR DESIGN* OR BIND* OR BOUND OR ATTACH* OR LINK* OR CONNECT* OR CONSTRUCT* OR BRANCH* OR BOND* OR FABRICAT* OR ‘SELF-ASSEMBL*’ OR ‘SELF-REPLICAT*’ OR ‘SELF-ORGANI*’ OR ‘DIRECTED-ASSEMBL*’ OR SYNTHETIC OR ARTIFICIAL OR ‘NON-NATURAL’ OR UNNATURAL OR ‘NON-GENETIC’ OR ORIGAMI
Structure = DOMAIN$ OR SYSTEM* OR MOTOR* OR MACHIN* OR DEVICE$ OR ARRAY$ OR POLYHEDR* OR CONJUGATE$ OR LADDER$ OR ‘*STRUCTURE$’ OR ‘*ROBOT*’ OR JUNCTION$ OR SCAFFOLD* OR TEMPLAT* OR TILE$ OR TILING$ OR LATTICE$ OR ‘STICKY END*’ OR ‘COHESIVE END*’ OR STAPL* OR ‘LOGIC GATE*’ OR CIRCUIT$
DNAFootnote 31 =‘DNA ACTUAT*’ OR ‘DNA NANOTECHNOLOGY’ OR ‘FOLDING DNA’ OR ‘DNA STRUCTURE’ OR ‘DNA ORIGAMI’ OR ‘DNA COMPUT*’ OR ‘DNA HYBRIDIZ*’ OR ‘*NUCLEIC ACID*’ OR ‘DOUBLE HELI*’ OR HELICES OR ‘*STRAND*’ OR ‘*NUCLEOTID*’ OR FOLDAMER$ OR APTAMER$
E1 = RIBONUCLEIC OR ‘*RNA’ OR RADIOTHERAPY OR SPECIES OR ‘*ORGANISM’ OR ORGAN$ OR ‘BIOLOGICAL AGENT$’ OR BIOMARKER$ OR ENHANC* OR ‘*BASE’ OR PAIR* OR ‘*NUCLEOTIDE SEQUENCE’ OR RECEPTOR$ OR ‘*WEAR’ OR CLONING OR BIOSENSOR$ OR SYMPTOM$ OR AGGLOMERATION OR PURIF* OR INFLAMMAT* OR ‘DNA SYNTHESIS’ OR HEMOGLOBIN OR HIV OR BIOACTIVE OR ‘DNA AMPLIFICATION’ OR ‘NUCLEIC ACID AMPLIFICATION’ OR BLOOD OR VITAMIN$ OR IMMUN* OR ANTIBODY OR ANTIGEN$ OR REAGENT$ OR ENCOD* OR VIRUS* OR BACTERI* OR GENE$ OR ‘GENE EXPRESSION’ OR HUMAN$ OR PATIENT$ OR LIFE OR ‘AMINO ACID$’ OR TISSUE$ OR ‘NON-NUCLEIC’
E2 = ‘GENE INTERACTION’ OR TRANSFECT* OR TRANSLOCAT* OR PHENOTYPE OR HYDROGEN OR ENHANCER$ OR EVOLUTION* OR EMBRYO* OR SEA OR FISH* OR ‘SIDE EFFECT$’ OR CULTURE OR FLOWER* OR CARBOHYDRATE$ OR INHIBITOR$ OR MOUSE OR MICE OR CO-EXPRESSION OR POLYMORPHISM OR NON-CODING OR COPY OR COPIES OR PARENT$ OR EXON*
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La, H.L., Bekkers, R. (2021). Science and Technology Relatedness: The Case of DNA Nanoscience and DNA Nanotechnology. In: Pyka, A., Lee, K. (eds) Innovation, Catch-up and Sustainable Development. Economic Complexity and Evolution. Springer, Cham. https://doi.org/10.1007/978-3-030-84931-3_3
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