Molassembler: Molecular Graph Construction, Modification, and Conformer Generation for Inorganic and Organic Molecules
Sign Up to like & getrecommendations! Published in 2020 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.0c00503
Abstract: We present the graph-based molecule software Molassembler for building organic and inorganic molecules. Molassembler provides algorithms for the construction of molecules built from any set of elements from the periodic table. In particular, poly-nuclear transition… read more here.
Keywords: molecular graph; molassembler molecular; construction; molecules molassembler ... See more keywords
Chemistry-informed molecular graph as reaction descriptor for machine-learned retrosynthesis planning
Sign Up to like & getrecommendations! Published in 2022 at "Proceedings of the National Academy of Sciences of the United States of America"
DOI: 10.1073/pnas.2212711119
Abstract: Significance Machine learning has achieved great success in retrosynthesis planning. We introduced chemical information, including NMR chemical shifts, bond energies, catalysts, and solvents into the descriptor of molecules and reactions and into molecular graphs to… read more here.
Keywords: reaction; machine; chemistry; molecular graph ... See more keywords
MGF6mARice: prediction of DNA N6-methyladenine sites in rice by exploiting molecular graph feature and residual block
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbac082
Abstract: DNA N6-methyladenine (6mA) is produced by the N6 position of the adenine being methylated, which occurs at the molecular level, and is involved in numerous vital biological processes in the rice genome. Given the shortcomings… read more here.
Keywords: dna; graph; molecular graph; mgf6marice ... See more keywords
Molormer: a lightweight self-attention-based method focused on spatial structure of molecular graph for drug-drug interactions prediction
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbac296
Abstract: Multi-drug combinations for the treatment of complex diseases are gradually becoming an important treatment, and this type of treatment can take advantage of the synergistic effects among drugs. However, drug-drug interactions (DDIs) are not just… read more here.
Keywords: molecular graph; prediction; method; attention ... See more keywords
Application of deep metric learning to molecular graph similarity
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Cheminformatics"
DOI: 10.1186/s13321-022-00595-7
Abstract: Graph based methods are increasingly important in chemistry and drug discovery, with applications ranging from QSAR to molecular generation. Combining graph neural networks and deep metric learning concepts, we expose a framework for quantifying molecular… read more here.
Keywords: molecular graph; metric learning; graph; similarity ... See more keywords