Michail Tsompanas' Outputs (6)

Evolutionary algorithms designing nanoparticle cancer treatments with multiple particle types (2021)
Journal Article

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

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

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

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

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.

Supplementary material: Evolutionary algorithms designing nano particle cancer treatments with multiple particle types (2021)
Other

Supplementary material: Evolutionary algorithms designing nano particle cancer treatments with multiple particle types