[Upstream sync] inoue0426/awesome-computational-biology (github) — 17 added, 6 modified #67
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---
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title: "AI4Bio Landscape Database"
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task: ""
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lineage_type: import
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upstream_source: https://github.com/inoue0426/awesome-computational-biology/blob/7a064bf0/docs/AI4BIO_LANDSCAPE.md
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upstream_sha: 7a064bf0
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imported_at: 2026-08-08
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prompt_class: catalogue
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upstream_changes: accepted
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author: upstream
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validated: false
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---
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# AI4Bio Landscape Database
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The landscape view treats the existing computational biology registry as a multidimensional database rather than a single hierarchical list.
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## Design goals
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- Keep the current curated resource records and generation pipeline intact.
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- Expose orthogonal facets so one resource can be explored by resource type, biological/ML task, data modality, organism, and domain tag.
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- Make the landscape useful without introducing a server or build-time dependency.
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- Keep the data model extensible for richer AI4Bio metadata over time.
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## Current facet model
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The landscape UI derives the following dimensions from `docs/data/resources.json`:
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| Dimension | Source field | Example values |
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|---|---|---|
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| Resource type | `type` | `database`, `benchmark`, `model`, `toolkit`, `api` |
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| Task | `tasks` | `drug-response-prediction`, `cell-type-annotation`, `molecular-generation` |
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| Modality | `modalities` | `transcriptomics`, `spatial-transcriptomics`, `protein-sequence` |
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| Organism | `organism` | `human`, `mouse`, `multi-species` |
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| Domain/tag | `tags` | `drug-discovery`, `single-cell`, `foundation-model` |
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These are deliberately treated as separate axes. A model can therefore be, for example, a `model` that performs `perturbation-prediction` on `single-cell-rna-seq` data for `human` and carry tags such as `drug-discovery` and `foundation-model`.
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## Recommended schema evolution
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The current schema is compatible with a richer landscape database. New fields should be added incrementally and only when they can be curated consistently.
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Suggested fields:
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| Field | Type | Purpose |
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|---|---|---|
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| `entities` | array of strings | Biological entities such as `gene`, `protein`, `compound`, `cell`, `disease` |
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| `methods` | array of strings | Method families such as `transformer`, `gnn`, `diffusion`, `optimal-transport` |
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| `organizations` | array of strings | Primary organizations responsible for the resource |
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| `year` | integer | Initial public release/publication year |
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| `github` | string | Source repository when distinct from the canonical landing page |
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| `documentation` | string | Documentation URL |
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| `maintenance_status` | string | Curated status such as `active`, `maintenance`, `archived`, `unknown` |
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| `last_checked` | string | Date the metadata/link was last manually or automatically checked |
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Avoid adding dynamic popularity metrics such as GitHub stars directly to canonical records unless a reproducible refresh pipeline is introduced. Such values become stale quickly and should be stored as generated metadata rather than curated facts.
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## Canonical-source policy
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At present, `README.md` is the canonical curated list, with generated YAML/JSON/CSV artifacts. The landscape page intentionally consumes `docs/data/resources.json` without changing that policy.
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A future migration may make `data/resources.yml` the canonical source once all README-only categorization semantics can be represented explicitly in structured fields. That migration should be a separate change because it changes contribution workflow and source-of-truth semantics.
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## Landscape page
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Open `docs/landscape.html` through GitHub Pages. It provides:
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- full-text search across names, descriptions, tasks, modalities, organisms, and tags;
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- filters for type, task, modality, organism, and tag;
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- summary counts for resources and major dimensions;
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- frequency bars recalculated for the current filtered result set;
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- direct resource and paper links;
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- client-side rendering with no additional dependencies.
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