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Mini-review on the applications and perspectives of a new simplex machine learning approach in chemistry and biology
1 , 2 , 3 , * 4
1  Quaid-i-Azam University, Department of Chemistry, Islamabad, Pakistan
2  University of Carthage, National Institute of Applied Sciences and Technology (INSAT), 1080, Tunis, Tunisia
3  University of Tunis El Manar, Faculté des Sciences de Tunis, Campus Universitaire, 2092 Tunis , Tunisia
4  University of Tunis El Manar. Pasteur Institute of Tunis. Laboratory of BioInformatics, bioMathematics and bioStatistics (BIMS), 1002, Tunis, Tunisia


This communication presents a two decades-updating on different applications of a new simulation method using simplex rule for smoothing regulation processes of several cooperative or competing components of complex mixture systems in biology and chemistry. Application fields covers different matter scales varying from atomes to ecosystems via molecular and biological organism levels. Simulation results issued from simplex approach helped for better understanding (i) inter-atomic regulation ways of molecular synthesis, (ii) organization metabolic pathways from chromatographic data, (iii) feeding behaviors of multi-prey foraging animal species. Application perspectives of the simplex machine-learning method are widely opened for highlighting multidirectional and multiscale regulation processes of polymorphism and diversification of multi-cluster complex systems from big data satisfying mass conservation principle.

Keywords: mass conservation; multidirectional processes; multiscale processes; regulation processes; simulation; smoothing