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Towards reproducible computational drug discovery
The reproducibility of experiments has been a long standing impediment for further scientific
progress. Computational methods have been instrumental in drug discovery efforts owing to …
progress. Computational methods have been instrumental in drug discovery efforts owing to …
Memory-assisted reinforcement learning for diverse molecular de novo design
In de novo molecular design, recurrent neural networks (RNN) have been shown to be
effective methods for sampling and generating novel chemical structures. Using a technique …
effective methods for sampling and generating novel chemical structures. Using a technique …
Human-in-the-loop assisted de novo molecular design
A de novo molecular design workflow can be used together with technologies such as
reinforcement learning to navigate the chemical space. A bottleneck in the workflow that …
reinforcement learning to navigate the chemical space. A bottleneck in the workflow that …
Industry-scale application and evaluation of deep learning for drug target prediction
Artificial intelligence (AI) is undergoing a revolution thanks to the breakthroughs of machine
learning algorithms in computer vision, speech recognition, natural language processing …
learning algorithms in computer vision, speech recognition, natural language processing …
Human-in-the-loop active learning for goal-oriented molecule generation
Machine learning (ML) systems have enabled the modelling of quantitative structure–
property relationships (QSPR) and structure-activity relationships (QSAR) using existing …
property relationships (QSPR) and structure-activity relationships (QSAR) using existing …
Enhancing reaction-based de novo design using a multi-label reaction class recommender
Reaction-based de novo design refers to the in-silico generation of novel chemical
structures by combining reagents using structural transformations derived from known …
structures by combining reagents using structural transformations derived from known …
TNFipred: a classification model to predict TNF-α inhibitors
Rheumatoid arthritis (RA), characterized by severe inflammation in the joint lining, is a
progressive, chronic, autoimmune disorder with high morbidity and mortality rates. There are …
progressive, chronic, autoimmune disorder with high morbidity and mortality rates. There are …
Direct steering of de novo molecular generation using descriptor conditional recurrent neural networks (crnns)
Deep learning has acquired considerable momentum over the past couple of years in the
domain of de-novo drug design. Particularly, transfer and reinforcement learning have …
domain of de-novo drug design. Particularly, transfer and reinforcement learning have …