Science Delight #8: Sci-Fi research? My firsthand experience with 'research' for novel writing.
- abrokepostgradrese
- Feb 16, 2025
- 9 min read
As a writer, exploring the exciting world of science can feel both thrilling and overwhelming. However, diving into these subjects often sparks creativity, especially when working on a novel. Recently, I immersed myself in some captivating fields: synthetic biology, neuromorphic computing, and cyberbiosecurity. I got so inspired that I ended up crafting a little literature review along the way. Let me share my insights, sprinkled with a bit of fun, and show how these exciting research areas can enrich sci-fi stories.
Exploring Synthetic Biology
Synthetic biology bridges biology and engineering, aiming to design new biological parts, devices, and systems. This field allows us to tinker with the very building blocks of life, and it is drawing interest from scientists and novelists alike.
Consider the possibility of designing microorganisms that can filter pollutants from water sources. Alternatively, imagine engineering cells that produce sustainable biofuels directly from waste materials. With the rise of CRISPR technology, gene editing has become more accessible. This raises the question: Could we engineer cells that fight off diseases like cancer or produce essential nutrients?
Ethical concerns surrounding synthetic biology open a treasure trove of narrative possibilities. What are the implications of tampering with nature? How do characters navigate the moral dilemmas posed by their groundbreaking inventions? This tension between progress and ethics can drive compelling character development and plot twists.
Injecting synthetic biology into your story can lead to dramatic plots. Picture a scientist who creates a revolutionary bacterium designed to absorb carbon dioxide but accidentally unleashes a strain that threatens ecosystems. Such scenarios showcase the enchanting yet perilous dance between innovation and the unforeseen consequences it can bring.
Diving Into Neuromorphic Computing
Neuromorphic computing mimics the way our brains work. By replicating brain architecture, researchers develop systems capable of processing information with incredible speed while using less power.
Think about a world where devices learn from human behavior much like a friend would. Researchers at IBM claimed their neuromorphic chip can enable computing that mimics human-like perception, potentially paving the way for more intuitive technology. This deep learning functionality can revolutionize our interaction with machines, allowing for machines that understand emotions and context.
You might illustrate a society where AI evolves into empathetic beings, challenging the divide between human and machine. What does consciousness look like in these new forms of intelligence? How do human characters react to machines that display intuition? Exploring these questions can lead to unforgettable stories.
Integrating neuromorphic computing in your narrative can enhance character dynamics. Characters that interact with AI machines capable of emotional understanding can lead to complex dialogue and unpredictable plot twists.
Understanding Cyberbiosecurity
As biotechnology and computing converge, the field of cyberbiosecurity has become increasingly vital. This sector focuses on safeguarding biological data and systems from cyber threats, especially in an age when hacking into genetic databases poses real risks.
The merging of biology and cybersecurity raises urgent questions. What if cyber criminals could alter an organism's DNA? Imagine a scenario where a hacker manipulates biological systems to unleash a genetically engineered virus. These alarming possibilities not only heighten tension but are also rich ground for thrilling narratives centered on bioethics and technological governance.
Picture a protagonist racing against time to prevent a cyberbioattack that threatens to unleash a slimy, fast-replicating pathogen. How do nations respond to such threats? What roles do hackers and government forces play in a world on the brink of disaster? The stakes could not be higher, making for gripping storytelling.
Cyberbiosecurity taps into current global concerns, adding a modern edge to your narrative. By weaving these issues into your story, you foster relatable conflicts and character journeys that resonate with readers.
Finding Joy in the Research Process
While working on my novel, I relished exploring these innovative fields. This research shifted my writing from routine to exciting, turning my narrative into a canvas painted with real science. I realized the importance of incorporating these groundbreaking concepts into my creative writing.
Each topic challenged me while offering unique opportunities to enrich my fictional world. By blending creativity with science, I pushed the limits of traditional sci-fi conventions.
Conducting research while crafting fiction deepened my understanding, equipping me with both facts and rich storytelling material. Insights from various articles helped me develop complex characters and intricate plotlines.
In a sense, I embraced my inner nerd while letting my creative side flourish. That's the beauty of intertwining research and writing; it opens a treasure trove of ideas and fresh perspectives.
A New Perspective on Storytelling
From synthetic biology to neuromorphic computing and cyberbiosecurity, these fields offer fertile ground for storytelling. Whether you explore the ethical dilemmas of scientific innovation, the evolution of intelligent machines, or the need to protect our biological future, there's ample material to inspire new sci-fi narratives.
As I finalize my novel, my research has helped shape its themes and enrich its narrative. This journey is not merely academic; it celebrates science and explores its implications for society.
So, fellow writers and readers, if you're tempted to investigate scientific realms, go for it! Embrace the adventure of blending research with storytelling. You might find that the science within your narrative adds both vibrancy and depth.
Remember, in the realm of fiction, the sky isn’t a limit. It’s just the beginning. Happy writing!
This is my little review:
Introduction
In recent years, three fields—synthetic biology, neuromorphic computing, and cyberbiosecurity—have advanced rapidly and begun to converge. The integration of these disciplines has not only reshaped our understanding of biological and computational systems but has also raised important questions about the dual-use potential of emerging technologies. This literature review provides a comprehensive overview of key theoretical and experimental developments that serve as the scientific foundation for the novel’s central concept: an engineered organism that integrates self-modifying genetic circuits with brain-inspired (neuromorphic) computational capabilities. By clearly delineating which aspects are grounded in current research and which are speculative extensions, this review aims to offer readers a robust framework for understanding both the science and the fiction behind the narrative.
Synthetic Biology and DNA-Based Computation
Synthetic biology is an interdisciplinary field that seeks to design and construct new biological parts, devices, and systems, or to redesign existing biological systems for useful purposes. Early work by Endy (2005) laid the groundwork for genomic engineering by demonstrating that DNA synthesis and modification could be performed with high precision. The advent of CRISPR/Cas9 gene-editing technology, as described by Doudna and Charpentier (2014), has since revolutionized the field by enabling rapid and cost-effective editing of genomes. Parallel to these advances, researchers have explored the use of DNA as a medium for computation. For example, Qian and Winfree (2011) demonstrated that DNA strand-displacement cascades could be used to build digital logic circuits, effectively using biomolecular interactions to process information.
In this novel, one key speculative element is a “designer” DNA module—conceptually derived from DNA-based logic circuits—that can initiate a cascade reaction to degrade or “corrupt” target genetic information. Although current research focuses on controlled gene expression and programmable biological networks (Church & Regis, 2012; Gibson et al., 2010), the idea of a self-propagating genetic “entropy” mechanism represents a deliberate extension of these principles.
Neuromorphic Computing and Bio-Inspired Hardware
Neuromorphic computing is a paradigm inspired by the structure and function of biological neural networks. Early theoretical work by Mead (1990) established the principles of designing electronic systems that mimic neuronal behavior. Subsequent projects such as IBM’s TrueNorth and the SpiNNaker system have demonstrated that large-scale spiking neural networks can perform complex computations with high energy efficiency (Furber, 2020; Furber, Galluppi, Temple, & Plana, 2014). These hardware systems simulate brain-like architectures, wherein information is processed in parallel through the coordinated firing of “neurons.”
Recent advances in materials science have extended neuromorphic concepts to devices that are not based solely on silicon. For example, graphene oxide–based synaptic memristors (Sahu, Jetty, & Jammalamadaka, 2020) and other organic neuromorphic devices (Xiao et al.,2024) mimic synaptic plasticity—the ability of connections between neurons to strengthen or weaken over time. Moreover, there is emerging research on the use of biological substrates to construct neuromorphic circuits. Work by Liu et al. (2024) illustrates how biomolecular circuits can be designed to perform computations analogous to neural networks. In our novel, these ideas are extrapolated into a scenario where living cells integrate neuromorphic genetic circuits to “learn” and adapt in real time. Although such integrated bio-computational systems are still in their infancy, the experimental and theoretical advances in neuromorphic computing offer a plausible basis for this speculative concept.
Cyberbiosecurity and Dual-Use Risks
The increasing accessibility of synthetic biology has raised significant biosecurity concerns. As DNA synthesis technologies become cheaper and more widely available, the risk that they might be misused for harmful purposes has grown (National Academies of Sciences, Engineering, and Medicine, 2018). Cyberbiosecurity—an emerging field at the intersection of cybersecurity and biosecurity—addresses vulnerabilities inherent in the digital and biological supply chains. Richardson et al. (2019) have emphasized that advances in synthetic biology may inadvertently facilitate the development of bioweapons if robust screening and regulatory measures are not maintained.
Recent studies have identified potential threats such as “DNA injection attacks,” in which malicious actors exploit vulnerabilities in the synthesis pipeline to introduce harmful sequences (Farbiash & Puzis, 2020). In the narrative, these risks are taken a step further by positing a scenario in which engineered DNA not only carries a dangerous biological payload but also interfaces directly with digital bio-data systems. This fusion of biological and digital threats illustrates the dual-use dilemma—a theme that is central to contemporary debates in both biosecurity and technology policy.
Adaptive and Self-Evolving Genetic Systems
Another innovative aspect of the narrative is the idea of adaptive, self-evolving genetic systems. Recent research in gene drives and genetic circuit design (Esvelt, Smidler, Catteruccia, & Church, 2014) has demonstrated that it is possible to engineer systems that can propagate specific traits through a population. These studies provide a theoretical basis for the development of genetic constructs that are capable of self-modification in response to environmental cues. In the novel, this concept is taken further by imagining an organism equipped with a built-in “entropy module” that deliberately induces mutations or degradation of targeted genetic information under certain conditions.
While the current state of technology does not allow for such precise and self-propagating genetic control, theoretical models—such as those proposed by Qian and Winfree (2011) and explored in adaptive gene drive research (Unckless, Clark, & Messer, 2017)—suggest that controlled error-prone DNA circuits may one day be feasible. This speculative leap, while not yet realized, is grounded in the broader context of ongoing advances in synthetic biology and genetic circuit design.
Distinguishing Science from Speculation
This review is designed to provide a clear demarcation between established scientific research and the speculative extrapolations that fuel the narrative. The factual basis of the story rests on well-documented technologies such as CRISPR/Cas9 gene editing (Doudna & Charpentier, 2014), DNA strand-displacement circuits (Qian & Winfree, 2011), and neuromorphic computing platforms (Furber, 2020). In contrast, the fictional elements—such as a self-corrupting DNA module and the integration of neuromorphic circuits within living organisms—represent imaginative extensions of these real-world technologies. By offering this theoretical background, the novel not only entertains but also educates its readers about the current state and potential future of these transformative fields.
Conclusion
The convergence of synthetic biology, neuromorphic computing, and cyberbiosecurity represents one of the most exciting and challenging frontiers in modern science. While significant progress has been made in each field individually, their integration opens new possibilities and risks. This literature review has outlined the scientific foundations that inspire the novel’s core concepts and has delineated the boundary between current knowledge and speculative innovation. Even if the novel does not achieve widespread commercial success, its theoretical framework is intended to contribute meaningfully to ongoing discussions about the ethical, security, and technological implications of emerging bioengineered systems.
References
1. Alon, U. (2007). An introduction to systems biology: Design principles of biological circuits. CRC Press.
2. Church, G. M., & Regis, E. (2012). Regenesis: How synthetic biology will reinvent nature and ourselves. Basic Books.
3. Doudna, J. A., & Charpentier, E. (2014). The new frontier of genome engineering with CRISPR-Cas9. Science, 346(6213), 1258096. https://doi.org/10.1126/science.1258096
4. Endy, D. (2005). Foundations for engineering biology. Nature, 438(7067), 449–453. https://doi.org/10.1038/nature04342
5. Esvelt, K. M., Smidler, A. L., Catteruccia, F., & Church, G. M. (2014). Concerning RNA-guided gene drives for the alteration of wild populations. eLife, 3, e03401. https://doi.org/10.7554/eLife.03401
6. Farbiash, D., & Puzis, R. (2020). Cyberbiosecurity: DNA injection attack in synthetic biology. arXiv preprint arXiv:2011.14224. https://arxiv.org/abs/2011.14224
7. Furber, S., & Bogdan, P. (Eds.) (2020). SpiNNaker: A spiking neural network architecture. Now Publishers Inc. https://library.oapen.org/handle/20.500.12657/47874
8. Furber, S.B., Galluppi, F., Temple, S., & Plana, L.A. (2014). The SpiNNaker Project. Proceedings of the IEEE, 102, 652-665.
9. Kitano H. (2002). Systems biology: a brief overview. Science (New York, N.Y.), 295(5560), 1662–1664. https://doi.org/10.1126/science.1069492
10. Maass, W. (1996). Lower bounds for the computational power of networks of spiking neurons. Neural Computation, 8(1), 1–40. https://doi.org/10.1162/neco.1996.8.1.1
11. Mead, C. (1990). Neuromorphic electronic systems. Proceedings of the IEEE, 78(10), 1629–1636. https://doi.org/10.1109/5.58356
12. National Academies of Sciences, Engineering, and Medicine. (2018). Biodefense in the age of synthetic biology. The National Academies Press.
13. National Academies of Sciences, Engineering, and Medicine. (2020). Safeguarding the bioeconomy: Confronting the dual-use challenge in the life sciences. The National Academies Press.
14. Qian, L., & Winfree, E. (2011). Scaling up digital circuit computation with DNA strand-displacement cascades. Science, 332(6034), 1196–1201. https://doi.org/10.1126/science.1200520
15. Richardson, L.C., Connell, N.D., Lewis, S.M., Pauwels, E., & Murch, R.S. (2019). Cyberbiosecurity: A Call for Cooperation in a New Threat Landscape. Frontiers in Bioengineering and Biotechnology, 7.
16. Sahu, D. P., Jetty, P., & Jammalamadaka, S. N. (2020). Graphene oxide based synaptic memristor device for neuromorphic computing. arXiv preprint arXiv:2012.13556. https://arxiv.org/abs/2012.13556
17. Schuman, C. D., Potok, T. E., Patton, R. M., et al. (2017). A survey of neuromorphic computing and neural networks in hardware. arXiv preprint arXiv:1705.06963. https://arxiv.org/abs/1705.06963
18. Liu, R., Liu, T., Liu, W., Luo, B., Li, Y., Fan, X., Zhang, X., Cui, W., & Teng, Y. (2024). SemiSynBio: A new era for neuromorphic computing. Synthetic and systems biotechnology, 9(3), 594–599. https://doi.org/10.1016/j.synbio.2024.04.013
19. Unckless, R. L., Clark, A. G., & Messer, P. W. (2017). Evolution of Resistance Against CRISPR/Cas9 Gene Drive. Genetics, 205(2), 827–841. https://doi.org/10.1534/genetics.116.197285
20. Voit, E. O. (2013). A first course in systems biology. Garland Science.
21. Xiao, Yike & Gao, Cheng & Jin, Juncheng & Sun, Weiling & Wang, Bowen & Bao, Yukun & Liu, Chen & Huang, Wei & Zeng, Hui & Yu, Yefeng. (2024). Recent Progress in Neuromorphic Computing from Memristive Devices to Neuromorphic Chips. Advanced Devices & Instrumentation. 5. 10.34133/adi.0044.
Comments