Datasets:

hugging-science
/

awesome-food-allergy-datasets

tags:
  - biology
  - medicine
  - food-allergy
  - immunology
  - drug-discovery
  - clinical-trials
  - genomics
  - proteomics
  - science
  - huggingscience
  - food-allergies
  - allergies
pretty_name: Awesome Food Allergy Datasets
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/awesome-food-allergy-datasets.tsv
dataset_info:
  features:
    - name: Name
      dtype: string
    - name: Category
      dtype: string
    - name: Description
      dtype: string
    - name: Task
      dtype: string
    - name: Data_Type
      dtype: string
    - name: Source
      dtype: string
    - name: Paper link
      dtype: string
    - name: Availability
      dtype: string
    - name: Contact
      dtype: string
  splits:
    - name: train
      num_examples: 72
  download_size: 24576
  dataset_size: 110592
  size_categories: <1K
license: apache-2.0
size_categories:
  - n<1K

Awesome Food Allergy Datasets

A curated collection of datasets, databases, and computational resources for food allergy research, allergen identification, drug development, and clinical applications.

🧬 Dataset Description

Dataset Summary

Food allergy affects over 220 million people worldwide. This repository serves as the first comprehensive, open collection of AI-ready datasets for food allergy research—spanning clinical trials, immunotherapy, genomics, proteomics, microbiome, and molecular data.

This dataset is a meta-dataset; it contains a curated list of pointers to various food allergy datasets, including their names, descriptions, data types, and direct links to their sources and corresponding research papers.

Our Goal

Enable researchers, ML practitioners, and the scientific community to advance AI applications in:

🏥 Early Detection & Risk Stratification
💊 Drug Design & Immunotherapy Development
🌿 Food Engineering & Hypoallergenic Product Development

🎯 Supported Tasks

This collection supports a wide range of tasks across different domains of food allergy research:

Allergen Identification & Prediction: Identifying and predicting allergenic potential of proteins.
Drug & Immunotherapy Development: Datasets for designing new drugs, analyzing immunotherapy outcomes, and mapping epitopes.
Patient Management & Clinical Decision Support: Clinical data to help in patient diagnosis, risk assessment, and management.
Food Product Development & Safety: Resources for ingredient analysis and developing hypoallergenic food products.
Computational Method Development: Benchmarking datasets for tasks like drug-target interaction and property prediction.
Cross-Reactivity Analysis: Datasets to study and predict cross-reactivity between different allergens.

🧱 Dataset Structure

Data Instances

Each instance in the dataset is a pointer to a specific food allergy resource, providing metadata about it.

Example:

{
  "Name": "SDAP 2.0",
  "Category": "Drug & Immunotherapy Development",
  "Description": "SDAP is a Web server that integrates a database of allergenic proteins with various computational tools that can assist structural biology studies related to allergens. SDAP is an important tool in the investigation of the cross-reactivity between known allergens, in testing the FAO/WHO allergenicity rules for new proteins, and in predicting the IgE-binding potential of genetically modified food proteins.",
  "Task": "Drug Design, Structural Analysis, Epitope Mapping, Cross-Reactivity Modeling",
  "Data_Type": "Molecular",
  "Source": "https://fermi.utmb.edu/",
  "Paper link": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10509899/",
  "Availability": "Open source",
  "Contact": null
}

Data Fields

Field Name	Type	Description
Name	string	The official name of the dataset or resource.
Category	string	The primary research area the dataset belongs to (e.g., Drug Development).
Description	string	A detailed summary of the dataset's contents and purpose.
Task	string	Specific machine learning or research tasks supported by the data.
Data_Type	string	The type of data contained (e.g., Molecular, Clinical, Mixed).
Source	string	A direct URL to access the dataset or resource.
Paper link	string	A URL to the primary research paper or documentation for the dataset.
Availability	string	The access status of the dataset (e.g., Open source, Gated).
Contact	string	Contact information for the dataset curators, if available.

🧩 Dataset Creation

This collection was manually curated by reviewing scientific literature, open data repositories, and clinical trial databases.
Each entry was selected for its relevance to food allergy research and its potential for use in computational and artificial intelligence applications.

The goal was to create a centralized, comprehensive, and accessible catalog to accelerate research in the field.

⚖️ License

The dataset collection itself is licensed under the Apache License 2.0.
However, the individual datasets listed within this collection are subject to their own licenses.
Please consult the Source and Availability fields for each dataset to determine its specific license and usage terms.