transformerCPI
importedtherapeutics/transformercpi
TransformerCPI: Improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments(BIOINFORMATICS 2020)…
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Therapeutics
- Subcategory
- unknown
- License
- Apache-2.0(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/lifanchen-simm/transformerCPI
- Documentation
- unknown
- Tags
- compound-protein-interaction · drug-discovery · drug-target-identification · self-attention · structure-free-virtual-sreening · transformercpi
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- ADASTself-attention
[IEEE TETCI] "ADAST: Attentive Cross-domain EEG-based Sleep Staging Framework with Iterative Self-Training"
- AttnSleepself-attention
[TNSRE 2021] "An Attention-based Deep Learning Approach for Sleep Stage Classification with Single-Channel EEG"
- ECGTransFormself-attention
[Biomedical Signal Processing and Control] ECGTransForm: Empowering adaptive ECG arrhythmia classification framework with bidirectional transformer
- AI-Binddrug-discovery
Interpretable AI pipeline improving binding predictions for novel protein targets and ligands
- AI-Binddrug-discovery
Interpretable AI pipeline improving binding predictions for novel protein targets and ligands
- allegrodrug-discovery
Allegro is a code for building highly scalable E(3)-equivariant interatomic potentials
- api.github.com/repos/lifanchen-simm/transformerCPIretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2022-06-30, 157 stars, license reported as Apache-2.0. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/62.json→ .entries["transformercpi"]
Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.