4 citations · 6 across the 4 of their papers we have counts for
6 papers
Towards open-ended evolutionary simulator for developing novel tumour drug delivery systems
Igor Balaz, Tara Petric, Namid Stillman
Tumours behave as moving targets that can evade chemotherapeutic treatments by rapidly acquiring resistance via various mechanisms. In Balaz et al. (2021, Biosystems; 199:104290) w…
Evolutionary computational platform for the automatic discovery of nanocarriers for cancer treatment
Namid Stillman, Igor Balaz, Antisthenis Tsompanas +5
We present the EVONANO platform for the evolution of nanomedicines with application to anti-cancer treatments. EVONANO includes a simulator to grow tumours, extract representative…
Evolving Nano Particle Cancer Treatments with Multiple Particle Types
Michail-Antisthenis Tsompanas, Larry Bull, Andrew Adamatzky +1
Evolutionary algorithms have long been used for optimization problems where the appropriate size of solutions is unclear a priori. The applicability of this methodology is here inv…
Novelty search employed into the development of cancer treatment simulations
Michail-Antisthenis Tsompanas, Larry Bull, Andrew Adamatzky +1
Conventional optimization methodologies may be hindered when the automated search is stuck into local optima because of a deceptive objective function landscape. Consequently, open…
Utilizing Differential Evolution into optimizing targeted cancer treatments
Michail-Antisthenis Tsompanas, Larry Bull, Andrew Adamatzky +1
Working towards the development of an evolvable cancer treatment simulator, the investigation of Differential Evolution was considered, motivated by the high efficiency of variatio…
Haploid-Diploid Evolution: Nature's Memetic Algorithm
Michail-Antisthenis Tsompanas, Larry Bull, Andrew Adamatzky +1
This paper uses a recent explanation for the fundamental haploid-diploid lifecycle of eukaryotic organisms to present a new memetic algorithm that differs from all previous known w…