- DeepMPF: deep learning framework for predicting drug–target interactions based on multi-modal representation with meta-path semantic analysis | Journal of Translational Medicine | Full Text (biomedcentral.com)
- From big data to complex network: a navigation through the maze of drug–target interaction – ScienceDirect
- MCL-DTI: using drug multimodal information and bi-directional cross-attention learning method for predicting drug–target interaction | BMC Bioinformatics (springer.com)
- AI-powered therapeutic target discovery: Trends in Pharmacological Sciences (cell.com)
- Metapath-based heterogeneous bioinformatics network dataset (scidb.cn)
- Mining drug-target interactions from biomedical literature using chemical and gene descriptions based ensemble transformer model (biorxiv.org)
- facebookresearch/bio-lm: We evaluate many models used for biomedical and clinical nlp tasks, and train new models that perform much better. (github.com)
- Mining connections between chemicals, proteins, and diseases extracted from Medline annotations – PubMed (nih.gov)
- Chemotext: A Publicly Available Web Server for Mining Drug–Target–Disease Relationships in PubMed | Journal of Chemical Information and Modeling (acs.org)
- DNorm: Disease Named Entity Recognition and Normalization (nih.gov)
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