In this paper, we improve the results based on a Neural Network-based model that predicts an enzyme (Aldose Reductase) inhibitory activity of a group of compounds. The improvement is due to the judicial selection of ensembles of trained Neural Networks to contribute to the final model. The method is validated on a family of compounds that is different from the families which were used in the training of the model. The results confirm an accurate, chemical-family-independent method that can predict Aldose Reductase inhibitory activity with excellent accuracy
Aldose reductase (ALR2) is a target enzyme for the treatment of diabetic complications. Owing to the...
Evolutionary computation provides a useful method for training neural networks in the face of multip...
Acetylcholinesterase inhibition was modeled for a set of 136 tacrine analogues using Bayesian-regula...
The DFT-B3LYP method, with the base set 6-31G (d), was used to calculate several quantum chemical de...
AbstractThe DFT-B3LYP method, with the base set 6-31G (d), was used to calculate several quantum che...
Aldose Reductase (AR) is the polyol pathway key enzyme which converts glucose to sorbitol. High gluc...
In this paper, we propose an artificial neural network approach to determine the quantitative struct...
Acetylcholine esterase (AChE) is one of the targeted enzymes in the therapy of important neurodegene...
In this article, in the first part, we propose an artificial neural network-based intelligent techni...
Diabetes mellitus is a chronic metabolic disease involving the failure to regulate glucose blood lev...
International audienceThe selection of optimal enzyme concentration in multienzyme cascade reactions...
We have used SOM and grid 3D and 4D QSAR schemes for modeling the activity of a series of dihydrofol...
AbstractCombinations of multiple linear regressions, genetic algorithms and artificial neural networ...
Classification of various compounds into their respective biological activity classes is important i...
The computer-automated structure evaluation program has been used to study 482 compounds relevant to...
Aldose reductase (ALR2) is a target enzyme for the treatment of diabetic complications. Owing to the...
Evolutionary computation provides a useful method for training neural networks in the face of multip...
Acetylcholinesterase inhibition was modeled for a set of 136 tacrine analogues using Bayesian-regula...
The DFT-B3LYP method, with the base set 6-31G (d), was used to calculate several quantum chemical de...
AbstractThe DFT-B3LYP method, with the base set 6-31G (d), was used to calculate several quantum che...
Aldose Reductase (AR) is the polyol pathway key enzyme which converts glucose to sorbitol. High gluc...
In this paper, we propose an artificial neural network approach to determine the quantitative struct...
Acetylcholine esterase (AChE) is one of the targeted enzymes in the therapy of important neurodegene...
In this article, in the first part, we propose an artificial neural network-based intelligent techni...
Diabetes mellitus is a chronic metabolic disease involving the failure to regulate glucose blood lev...
International audienceThe selection of optimal enzyme concentration in multienzyme cascade reactions...
We have used SOM and grid 3D and 4D QSAR schemes for modeling the activity of a series of dihydrofol...
AbstractCombinations of multiple linear regressions, genetic algorithms and artificial neural networ...
Classification of various compounds into their respective biological activity classes is important i...
The computer-automated structure evaluation program has been used to study 482 compounds relevant to...
Aldose reductase (ALR2) is a target enzyme for the treatment of diabetic complications. Owing to the...
Evolutionary computation provides a useful method for training neural networks in the face of multip...
Acetylcholinesterase inhibition was modeled for a set of 136 tacrine analogues using Bayesian-regula...