metadata

dataset_info:
  features:
    - name: Canonicalized SMILES
      dtype: string
    - name: Canonicalized Flavor
      dtype: string
    - name: Original Labels
      dtype: string
    - name: Source
      dtype: string
  splits:
    - name: train
      num_bytes: 1970859
      num_examples: 22038
    - name: test
      num_bytes: 420863
      num_examples: 4722
    - name: validation
      num_bytes: 419548
      num_examples: 4723
  download_size: 778401
  dataset_size: 2811270
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
      - split: validation
        path: data/validation-*
task_categories:
  - text-classification
tags:
  - chemistry
size_categories:
  - 10K<n<100K

FartDB

Composite dataset of 31,483 molecules and their taste (sweet, bitter, umami, sour, salty, miscellaneous).

Dataset Details

Dataset Description

Curated by: Fart Labs
License: [More Information Needed]

Dataset Sources

Gradinaru Teodora-Cristiana, Madalina Petran, Dorin Dragos, and Marilena Gilca. "PlantMolecularTasteDB: A Database of Taste Active Phytochemicals." Frontiers in Pharmacology 2022; 12:3804. doi: 10.3389/fphar.2021.751712

Neelansh Garg†, Apuroop Sethupathy†, Rudraksh Tuwani†, Rakhi NK†, Shubham Dokania†, Arvind Iyer†, Ayushi Gupta†, Shubhra Agrawal†, Navjot Singh†, Shubham Shukla†, Kriti Kathuria†, Rahul Badhwar, Rakesh Kanji, Anupam Jain, Avneet Kaur, Rashmi Nagpal, and Ganesh Bagler*, "FlavorDB: A database of flavor molecules," Nucleic Acids Research, gkx957, (2017). †Equal contribution *Corresponding Author

Rojas, C., Ballabio, D., Pacheco Sarmiento, K., Pacheco Jaramillo, E., Mendoza, M., & García, F. (2021). ChemTastesDB: A Curated Database of Molecular Tastants (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5747393

Uses

Direct Use

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Out-of-Scope Use

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Dataset Structure

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Dataset Creation

Curation Rationale

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Source Data

Data Collection and Processing

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Who are the source data producers?

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Personal and Sensitive Information

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Bias, Risks, and Limitations

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Recommendations

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