Philip Doganis
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Time series sales forecasting for short shelf-life food products based on artificial neural networks and evolutionary computing
P Doganis, A Alexandridis, P Patrinos, H Sarimveis
Journal of food engineering 75 (2), 196-204, 2006
The eNanoMapper database for nanomaterial safety information
N Jeliazkova, C Chomenidis, P Doganis, B Fadeel, R Grafström, B Hardy, ...
Beilstein journal of nanotechnology 6 (1), 1609-1634, 2015
Optimal scheduling in a yogurt production line based on mixed integer linear programming
P Doganis, H Sarimveis
Journal of Food Engineering 80 (2), 445-453, 2007
NanoSolveIT Project: Driving nanoinformatics research to develop innovative and integrated tools for in silico nanosafety assessment
A Afantitis, G Melagraki, P Isigonis, A Tsoumanis, DD Varsou, ...
Computational and Structural Biotechnology Journal 18, 583-602, 2020
An adaptive model predictive control configuration for production–inventory systems
E Aggelogiannaki, P Doganis, H Sarimveis
International Journal of Production Economics 114 (1), 165-178, 2008
A classification technique based on radial basis function neural networks
H Sarimveis, P Doganis, A Alexandridis
Advances in Engineering Software 37 (4), 218-221, 2006
Optimal production scheduling for the dairy industry
P Doganis, H Sarimveis
Annals of Operations Research 159, 315-331, 2008
A combined model predictive control and time series forecasting framework for production-inventory systems
P Doganis, E Aggelogiannaki, H Sarimveis
International Journal of Production Research 46 (24), 6841-6853, 2008
Metadata stewardship in nanosafety research: Community-driven organisation of metadata schemas to support FAIR nanoscience data
AG Papadiamantis, FC Klaessig, TE Exner, S Hofer, N Hofstaetter, ...
Nanomaterials 10 (10), 2033, 2020
Development of Deep Learning Models for Predicting the Effects of Exposure to Engineered Nanomaterials on Daphnia magna
P Karatzas, G Melagraki, LJA Ellis, I Lynch, DD Varsou, A Afantitis, ...
Small 16 (36), 2001080, 2020
Current approaches and techniques in physiologically based pharmacokinetic (PBPK) modelling of nanomaterials
W Utembe, H Clewell, N Sanabria, P Doganis, M Gulumian
Nanomaterials 10 (7), 1267, 2020
Can an InChI for nano address the need for a simplified representation of complex nanomaterials across experimental and nanoinformatics studies?
I Lynch, A Afantitis, T Exner, M Himly, V Lobaskin, P Doganis, D Maier, ...
Nanomaterials 10 (12), 2493, 2020
Representing and describing nanomaterials in predictive nanoinformatics
E Wyrzykowska, A Mikolajczyk, I Lynch, N Jeliazkova, N Kochev, ...
Nature Nanotechnology 17 (9), 924-932, 2022
Jaqpot Quattro: a novel computational web platform for modeling and analysis in nanoinformatics
C Chomenidis, G Drakakis, G Tsiliki, E Anagnostopoulou, A Valsamis, ...
Journal of Chemical Information and Modeling 57 (9), 2161-2172, 2017
16 Mixed Integer Linear Programming Scheduling in the Food Industry
P Doganis, H Sarimveis
Optimization in food engineering, 305, 2008
A model predictive control and time series forecasting framework for supply chain management
P Doganis, E Aggelogiannaki, H Sarimveis
International Journal of Industrial and Manufacturing Engineering 2 (3), 315-319, 2008
The first eNanoMapper prototype: A substance database to support safe-by-design
N Jeliazkova, P Doganis, B Fadeel, R Grafström, J Hastings, V Jeliazkov, ...
2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 1-9, 2014
Optimization of power production through coordinated use of hydroelectric and conventional power units
P Doganis, H Sarimveis
Applied Mathematical Modelling 38 (7-8), 2051-2062, 2014
Machine learning predictions of concentration-specific aggregate hazard scores of inorganic nanomaterials in embryonic zebrafish
C Gousiadou, RL Marchese Robinson, M Kotzabasaki, P Doganis, ...
Nanotoxicology 15 (4), 446-476, 2021
Decision trees for continuous data and conditional mutual information as a criterion for splitting instances
G Drakakis, S Moledina, C Chomenidis, P Doganis, H Sarimveis
Combinatorial chemistry & high throughput screening 19 (5), 423-428, 2016
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