NCBI PubMed Central
open access
Graph Neural Networks Model Based on Atomic Hybridization for Predicting Drug Targets.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
Checking your browser - reCAPTCHA Checking your browser before accessing pmc.ncbi.nlm.nih.gov ... Click here if you are not automatically redirected after 5 seconds.
Related documents
- TensoGraph: a tensor-transformer framework for global-local drug synergy prediction on heterogeneous graphs.#13515
- Unified theory of atom-centered representations and message-passing machine-learning schemes#644932
- On Representing Linear Programs by Graph Neural Networks#228759
- Graph Neural Networks for Communication Networks: Context, Use Cases and Opportunities#209945
- TaLK: Text-attributed Graph Dataset Distillation via Coupling Language Model with Graph-Aware Kernel#821927
Record · ID 14959 · SHA-256 934b4ae7e91a33af
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive