MACHINE LEARNING METHODS TO FIND ATOM-TO-ATOM MAPPING IN REACTIONS

In this work we propose a novel approach to find optimal atom-atom mapping (AAM) - correspondence between atoms of substrats and products, that is based on application of machine learning techniques.

Exploring semantic analysis of biomedical texts for identification of drugs with similar therapeutic effects

Exploring semantic analysis of biomedical texts for identification of drugs with similar therapeutic effects

DEVELOPMENT OF ALGORITHM FOR CREATING ATOM-ATOMIC MAPPING USING "NAIVE" BAYES MACHINE LEARNING METHOD

In this work we propose a novel approach to find optimal the atom-atom mapping (AAM) that is based on application of machine learning techniques.

AUTOMATIC SYSTEM FOR PREDICTION OF OPTIMAL CONDITION FOR HYDROGENATION REACTIONS

Prediction of tautomeric equilibria: QSAR vs quantum chemistry

Asessment of optimal reaction conditions: deprotection in catalytic hydrogenation conditions

Prediction of tautomer equilibrium constants using the Condensed Graphs of Reaction approach

The Condensed Graph of Reaction Approach ? an Efficient Tool of Reactions Mining