106 lines
2.4 KiB
YAML
106 lines
2.4 KiB
YAML
---
|
|
title: "Canonical vocabulary for new AI4Bio enrichment metadata."
|
|
task: ""
|
|
lineage_type: import
|
|
upstream_source: https://github.com/inoue0426/awesome-computational-biology/blob/7a064bf0/data/vocabulary.yml
|
|
upstream_sha: 7a064bf0
|
|
imported_at: 2026-08-08
|
|
prompt_class: unknown
|
|
upstream_changes: accepted
|
|
author: upstream
|
|
validated: false
|
|
---
|
|
|
|
# Canonical vocabulary for new AI4Bio enrichment metadata.
|
|
#
|
|
# These values are enforced only for fields explicitly added through
|
|
# data/enrichment.yml. README-derived legacy values remain backward compatible.
|
|
# Canonical terms use lowercase kebab-case.
|
|
|
|
version: 1
|
|
|
|
controlled_fields:
|
|
entities:
|
|
- cell
|
|
- compound
|
|
- disease
|
|
- drug
|
|
- gene
|
|
- genome
|
|
- molecule
|
|
- organism
|
|
- pathway
|
|
- phenotype
|
|
- protein
|
|
- protein-complex
|
|
- regulatory-element
|
|
- tissue
|
|
- transcript
|
|
- variant
|
|
|
|
methods:
|
|
- autoencoder
|
|
- contrastive-learning
|
|
- convolutional-neural-network
|
|
- diffusion
|
|
- generative-model
|
|
- geometric-deep-learning
|
|
- graph-neural-network
|
|
- knowledge-graph
|
|
- language-model
|
|
- message-passing-neural-network
|
|
- multi-agent-system
|
|
- optimal-transport
|
|
- recurrent-neural-network
|
|
- reinforcement-learning
|
|
- retrieval-augmented-generation
|
|
- self-supervised-learning
|
|
- state-space-model
|
|
- supervised-learning
|
|
- transformer
|
|
- unsupervised-learning
|
|
- variational-autoencoder
|
|
|
|
modalities:
|
|
- cell-painting
|
|
- chemical-structure
|
|
- clinical
|
|
- dna-sequence
|
|
- electronic-health-record
|
|
- epigenomics
|
|
- genomics
|
|
- histopathology
|
|
- imaging
|
|
- knowledge-graph
|
|
- metabolomics
|
|
- molecular-structure
|
|
- multi-omics
|
|
- protein-sequence
|
|
- proteomics
|
|
- rna-sequence
|
|
- single-cell-rna-seq
|
|
- spatial-transcriptomics
|
|
- transcriptomics
|
|
|
|
tasks:
|
|
- batch-correction
|
|
- cell-type-annotation
|
|
- classification
|
|
- dimensionality-reduction
|
|
- docking
|
|
- drug-response-prediction
|
|
- drug-target-interaction
|
|
- foundation-model-pretraining
|
|
- gene-regulatory-network-inference
|
|
- imputation
|
|
- link-prediction
|
|
- molecular-generation
|
|
- perturbation-prediction
|
|
- protein-function-prediction
|
|
- protein-sequence-design
|
|
- regression
|
|
- representation-learning
|
|
- structure-prediction
|
|
- trajectory-inference
|
|
- virtual-screening
|