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All Outputs (6)

Evolutionary algorithms designing nanoparticle cancer treatments with multiple particle types (2021)
Journal Article
Tsompanas, M. A., Bull, L., Adamatzky, A., & Balaz, I. (2021). Evolutionary algorithms designing nanoparticle cancer treatments with multiple particle types. IEEE Computational Intelligence Magazine, 16(4), 85-99. https://doi.org/10.1109/MCI.2021.3108306

There is a rich history of evolutionary algorithms tackling optimization problems where the most appropriate size of solutions, namely the genome length, is unclear a priori. Here, we investigated the applicability of this methodology on the problem... Read More about Evolutionary algorithms designing nanoparticle cancer treatments with multiple particle types.

Mem-fractive properties of mushrooms (2021)
Journal Article
Beasley, A. E., Abdelouahab, M. S., Lozi, R., Tsompanas, M. A., Powell, A., & Adamatzky, A. (2022). Mem-fractive properties of mushrooms. Bioinspiration and Biomimetics, 16(6), Article 066026. https://doi.org/10.1088/1748-3190/ac2e0c

Memristors close the loop for I-V characteristics of the traditional, passive, semi-conductor devices. A memristor is a physical realisation of the material implication and thus is a universal logical element. Memristors are getting particular intere... Read More about Mem-fractive properties of mushrooms.

Evolutionary computational platform for the automatic discovery of nanocarriers for cancer treatment (2021)
Journal Article
Stillman, N. R., Balaz, I., Tsompanas, M. A., Kovacevic, M., Azimi, S., Lafond, S., …Hauert, S. (2021). Evolutionary computational platform for the automatic discovery of nanocarriers for cancer treatment. npj Computational Materials, 7(1), Article 150. https://doi.org/10.1038/s41524-021-00614-5

We present the EVONANO platform for the evolution of nanomedicines with application to anti-cancer treatments. Our work aims to decrease both the time and cost required to develop nanoparticle designs. EVONANO includes a simulator to grow tumours, ex... Read More about Evolutionary computational platform for the automatic discovery of nanocarriers for cancer treatment.

Metameric representations on optimization of nano particle cancer treatment (2021)
Journal Article
Tsompanas, M. A., Bull, L., Adamatzky, A., & Balaz, I. (2021). Metameric representations on optimization of nano particle cancer treatment. Biocybernetics and Biomedical Engineering, 41(2), 352-361. https://doi.org/10.1016/j.bbe.2021.02.002

In silico evolutionary optimization of cancer treatment based on multiple nano-particle (NP) assisted drug delivery systems was investigated in this study. The use of multiple types of NPs is expected to increase the robustness of the treatment, due... Read More about Metameric representations on optimization of nano particle cancer treatment.

Neural networks predicting microbial fuel cells output for soft robotics applications (2021)
Journal Article
Tsompanas, M. A., You, J., Philamore, H., Rossiter, J., & Ieropoulos, I. (2021). Neural networks predicting microbial fuel cells output for soft robotics applications. Frontiers in Robotics and AI, 8, Article 633414. https://doi.org/10.3389/frobt.2021.633414

The development of biodegradable soft robotics requires an appropriate eco-friendly source of energy. The use of Microbial Fuel Cells (MFCs) is suggested as they can be designed completely from soft materials with little or no negative effects to the... Read More about Neural networks predicting microbial fuel cells output for soft robotics applications.