{"url":"/method/mxmnet","slug":"mxmnet","name":"MXMNet","full_name":"Multiplex Molecular Graph Neural Network","full_name_withheld":false,"description_markdown":"The **Multiplex Molecular Graph Neural Network (MXMNet)** is an approach for the representation learning of molecules. The molecular interactions are divided into two categories: local and global. Then a two-layer multiplex graph $G = \\\\{ G_{l}, G_{g} \\\\}$ is constructed for a molecule. In $G$, the local layer $G_{l}$ only contains the local connections that mainly capture covalent interactions, and the global layer $G_{g}$ contains the global connections that cover non-covalent interactions. MXMNet uses the Multiplex Molecular (MXM) module that contains a novel angle-aware message passing operated on $G_{l}$ and an efficient message passing operated on $G_{g}$.","description_state":"present","introduced_year":null,"introduced_by":{"title":"Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures","paper":"/paper/molecular-mechanics-driven-graph-neural","first_author":"Shuo Zhang","n_authors":3,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/molecular-mechanics-driven-graph-neural"},"source":{"url":"https://arxiv.org/abs/2011.07457v1","title":"Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"Graphs","area_id":"graphs","collection":"Graph Models","url":"/methods/category/graph-models","pwc_aliases":[]}],"n_papers_tagged":1,"archive_num_papers":1,"papers_newest_first":[{"paper":"/paper/molecular-mechanics-driven-graph-neural","title":"Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures","date":"2020-11-15","arxiv_id":"2011.07457","n_code_links":3,"syntology":null}],"papers_shown":1,"tasks":[{"task":"/task/drug-discovery","name":"Drug Discovery","papers":1},{"task":"/task/formation-energy","name":"Formation Energy","papers":1},{"task":"/task/graph-neural-network","name":"Graph Neural Network","papers":1}],"tasks_shown":3,"n_tasks":3,"usage_by_year":[{"year":"2020","papers":1}],"row_source":"methods_table","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/mxmnet"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}