# BioModels Systems Biology Models Scraper (`ninhothedev/biomodels-scraper`) Actor

$0.5/1K 🔥 BioModels Scraper! Grab curated systems-biology models, metadata, authors & publications from the EBI BioModels repository. No key. JSON, CSV, Excel or API in seconds. Feed a research pipeline or model database ⚡

- **URL**: https://apify.com/ninhothedev/biomodels-scraper.md
- **Developed by:** [ninhothedev](https://apify.com/ninhothedev) (community)
- **Categories:** Developer tools, AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.50 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## BioModels Systems Biology Models Scraper

Scrape curated **mathematical models of biological systems** from the [EBI BioModels](https://www.ebi.ac.uk/biomodels) repository — the reference database for reproducible, quantitative models in systems biology. Get **SBML file metadata**, **curation status**, **modelling approach**, and **full publication details** (title, journal, year, authors, link, synopsis) in one clean dataset. **No API key required.**

> Pricing: pay-as-you-go, roughly **~$0.5 per 1,000 models** in platform usage. BioModels content is released under **CC0** (public domain).

### What it does

Two modes:

- **`search`** — query BioModels by keyword (e.g. `glycolysis`, `circadian`, `apoptosis`). Each matching model is enriched with its full detail record.
- **`models`** — fetch explicit model IDs directly (e.g. `BIOMD0000000012`, `MODEL1234567890`).

### Input

| Field | Type | Description |
|-------|------|-------------|
| `mode` | select | `search` (keyword query) or `models` (explicit IDs). Default `search`. |
| `queries` | array | Keywords to search for. Prefilled `["glycolysis","circadian","apoptosis"]`. Used in `search` mode. |
| `modelIds` | array | Explicit BioModels IDs. Used in `models` mode. |
| `maxItems` | integer | Max models to scrape. Default `200`, max `3000`. |

#### Example input

```json
{
  "mode": "search",
  "queries": ["glycolysis", "circadian"],
  "maxItems": 100
}
```

### Output

One record per model:

```json
{
  "type": "model",
  "model_id": "BIOMD0000000012",
  "name": "Elowitz2000 - Repressilator",
  "description": "This model describes the deterministic version of the repressilator system.",
  "format": "SBML",
  "curation_status": "CURATED",
  "modelling_approach": "ordinary differential equation model",
  "submitter": "Nicolas Le Novere",
  "submission_id": "MODEL6615351360",
  "publication_title": "A synthetic oscillatory network of transcriptional regulators.",
  "publication_journal": "Nature",
  "publication_year": 2000,
  "publication_authors": ["M B Elowitz", "S Leibler"],
  "publication_link": "http://identifiers.org/pubmed/10659856",
  "publication_synopsis": "Networks of interacting biomolecules carry out many essential functions...",
  "main_file": "BIOMD0000000012_url.xml",
  "main_file_size": 43901,
  "additional_file_count": 15,
  "last_modified": "2024-08-21T18:29:21+00:00",
  "download_url": "https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000012",
  "url": "https://www.ebi.ac.uk/biomodels/BIOMD0000000012",
  "source": "biomodels",
  "scraped_at": "2026-08-11T00:00:00+00:00"
}
```

Download the raw SBML from `download_url` for direct simulation.

### Use cases

- **Systems biology** — bulk-collect curated ODE/stochastic models for a pathway or topic.
- **Model reuse** — find and reuse existing SBML models instead of rebuilding from scratch.
- **Quantitative biology teaching** — assemble worked example models with their source papers.
- **Reproducibility** — track curation status, provenance, and publication links for reproducible research.

### Related actors

- [Reactome Pathways Scraper](https://apify.com/ninhothedev/reactome-pathways-scraper)
- [KEGG Scraper](https://apify.com/ninhothedev/kegg-scraper)
- [STRING Interactions Scraper](https://apify.com/ninhothedev/string-interactions-scraper)
- [UniProt Scraper](https://apify.com/ninhothedev/uniprot-scraper)

### Notes

Data is served by the public BioModels REST API (no key). Please be considerate with request volume. BioModels content is CC0-licensed.

# Actor input Schema

## `mode` (type: `string`):

Choose 'search' to query BioModels by keyword and enrich each match with full detail, or 'models' to fetch explicit model IDs directly.

## `queries` (type: `array`):

Keywords to search BioModels for (used only in 'search' mode). Each query is paginated and its matching models are enriched with detail.

## `modelIds` (type: `array`):

Explicit BioModels IDs to fetch (used only in 'models' mode), e.g. BIOMD0000000012 or MODEL1234567890.

## `maxItems` (type: `integer`):

Maximum number of models to scrape across all queries or IDs.

## Actor input object example

```json
{
  "mode": "search",
  "queries": [
    "glycolysis",
    "circadian",
    "apoptosis"
  ],
  "modelIds": [
    "BIOMD0000000012"
  ],
  "maxItems": 200
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "queries": [
        "glycolysis",
        "circadian",
        "apoptosis"
    ],
    "modelIds": [
        "BIOMD0000000012"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("ninhothedev/biomodels-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "queries": [
        "glycolysis",
        "circadian",
        "apoptosis",
    ],
    "modelIds": ["BIOMD0000000012"],
}

# Run the Actor and wait for it to finish
run = client.actor("ninhothedev/biomodels-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "queries": [
    "glycolysis",
    "circadian",
    "apoptosis"
  ],
  "modelIds": [
    "BIOMD0000000012"
  ]
}' |
apify call ninhothedev/biomodels-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,ninhothedev/biomodels-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/Pll8kL2giZ4OsexBB/builds/YMmjmPOmzgGLOdIs5/openapi.json