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A Method for Molecular Design Based on Linear Regression and Integer Programming
2022 12th International Conference on Bioscience, Biochemistry and Bioinformatics
Recently a novel framework has been proposed for designing the molecular structure of chemical compounds using both artificial neural networks (ANNs) and mixed integer linear programming (MILP). In the framework, we first define a feature vector f (C) of a chemical graph C and construct an ANN that maps x = f (C) to a predicted value η(x) of a chemical property π to C. After this, we formulate an MILP that simulates the computation process of f (C) from C and that of η(x) from x. Given a targetdoi:10.1145/3510427.3510431 fatcat:i4rf6be7g5gnrltpt4ahhhmifi