NCBI PubMed Central
open access
Drug target prediction from perturbation transcriptomics via a biological function-guided hypergraph siamese network.
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.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- scTACL: a multitask topology-aware contrastive learning approach for single-cell transcriptomics analysis.#312561
- Asymmetric Focal Loss Improves Graph Neural Network Prediction of Drug-Drug Interactions#349625
- ScanNet: Single-cell annotation informed by transcriptional regulation Network via iterative heterogeneous graph learning#434555
- Network-based prediction of drug combinations with quantum annealing#1063824
- Protein language model embeddings improve HIV drug resistance prediction: a comprehensive benchmark with attention-based interpretability.#222925
Record · ID 440782
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