… Here, we review methods for achieving inverse design, which aims to … of machine learning,
have resulted in a fertile exchange of ideas, where approaches to inverse molecular design …

… In this paper, we reviewed the current progress of applying machine learning to elements
of molecular design problems across different scales. As seen, however, the current CMD …

Machine learning (ML) has become a crucial component of early drug discovery. This
research area has been fueled by two main factors. The first is the fast-growing availability of …

… As mentioned above, our system makes use of machine learning techniques to deal with
the SAR problem. The term 'learning', in everyday language, is used in a somewhat broad and …

… Through supervised learning, our machine learning (ML) models can build up the structure-…
We explore several expressions for molecule structures, ie, images, ASCII strings, descriptors…

… Recently, his group has been working on employing modern artificial intelligence/machine
learning techniques for molecular/drug design and healthcare. He is a recipient of awards …

… in machine learning models for molecule design. We start with a brief review of the mainstream
molecule … Then we summarize all the existing molecule design problems into several …

… molecular simulation and machine learning could provide alternative tools for the molecular
design … Generally, researchers adopt a series of molecular design schemes combined with …

… The use of machine learning in computational molecular design has great … by machine-learning-assisted
polymer chemistry. This discovery was made by the interplay between machine …

… -aided molecular design/screening method is developed in this work for the design and …
In this method, the odor of the molecules are predicted using a data driven machine learning …