Added all sources to ReadME.md

Filled out the ReadME.
Added all sources and explained data curation process.

README.md

@@ -42,14 +42,18 @@ tags:
 
 <!-- Provide a quick summary of the dataset. -->
 
-Composite dataset of 31,483 molecules and their taste (sweet, bitter, umami, sour, salty, miscellaneous). 
+Composite dataset of 19,478 molecules and their taste (sweet, bitter, umami, sour, undefined). 
 
 ## Dataset Details
 
 ### Dataset Description
 
 <!-- Provide a longer summary of what this dataset is. -->
+FartDB is a curated dataset drawn from five data sources: FlavorDB, PlantMolecularTasteDB, ChemTastesDB, Tas2R Agonists DB and Scifinder.
+A canonicalized SMILES is mapped to one of five flavor categories: sweet, bitter, umami, sour, undefined. Salty molecules are not considered as only a small number of compounds have this taste. 
+The dataset was enriched with other descriptors from PubChem where available and when multiple datasets contained the same SMILES/Taste data point, these duplicates were removed. 
 
+Note that a small number (< 5) of canonicalized SMILES in the dataset may not form valid molecules. These may need to be removed before use. 
 
 
 - **Curated by:** Fart Labs
@@ -59,21 +63,41 @@ Composite dataset of 31,483 molecules and their taste (sweet, bitter, umami, sou
 
 <!-- Provide the basic links for the dataset. -->
 
-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
+FlavorDB:
+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
+<https://doi.org/10.1093/nar/gkx957>
 
-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
+PlantMolecularTasteDB:
+Gradinaru Teodora-Cristiana, Madalina Petran, Dorin Dragos, and Marilena Gilca. "PlantMolecularTasteDB: A Database of Taste Active Phytochemicals." *Frontiers in Pharmacology* 2022; 12:3804. 
+<https://doi.org/10.3389/fphar.2021.751712>
 
-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>
+ChemTastesDB:
+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>
 
+Tas2R Agonists DB:
+Sebastian Bayer, Ariane Isabell Mayer, Gigliola Borgonovo, Gabriella Morini, Antonella Di Pizio, and Angela Bassoli, Journal of Agricultural and Food Chemistry 2021 69 (46), 13916-13924, 
+<https://doi.org/10.1021/acs.jafc.1c05057>
+
+Scifinder: 
+<https://scifinder.cas.org> (Accessed May 5th 2024)
+
+Umami Compounds (manually added):
+B. Suess, D. Festring, T. Hofmann, 15 - Umami compounds and taste enhancers, Editor(s): J.K. Parker, J.S. Elmore, L. Methven, In Woodhead Publishing Series in Food Science, Technology and Nutrition, Flavour Development, Analysis and Perception in Food and Beverages, Woodhead Publishing, 2015, Pages 331-351, ISBN 9781782421030,
+<https://doi.org/10.1016/B978-1-78242-103-0.00015-1>
 
 ## Uses
 
 <!-- Address questions around how the dataset is intended to be used. -->
 
+This dataset is intended for the training of machine learning models, in particular transformer models trained on SMILES such as ChemBERTa. 
+
 ### Direct Use
 
 <!-- This section describes suitable use cases for the dataset. -->
 
+This dataset has been used to finetune ChemBERTa to be able to predict the flavor from an arbitrary SMILES input. 
+
 [More Information Needed]
 
 ### Out-of-Scope Use
@@ -85,8 +109,12 @@ Rojas, C., Ballabio, D., Pacheco Sarmiento, K., Pacheco Jaramillo, E., Mendoza,
 ## Dataset Structure
 
 <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
+The first two columns contain: "Canonicalized SMILES" as canonicalized by RDKit and the "Canonicalized Flavor " (sweet, sour, umami, bitter, undefined). 
+"Original Labels": Some databases were labelled by professional tasters or contain labels that had to be canonicalized into one of the four flavor categories defined by us (e.g. "honey" --> "sweet"). These original labels are given for data transparency. 
+"Source": which database this data point derives from 
 
-[More Information Needed]
+PubChem descriptors: Where available, the dataset was enriched with descriptors accessible through the PubChem API. 
+"PubChemID", "IUPAC Name", "Molecular Formula", "Molecular Weight", "InChI", "InChI Key"
 
 ## Dataset Creation
 
@@ -94,17 +122,30 @@ Rojas, C., Ballabio, D., Pacheco Sarmiento, K., Pacheco Jaramillo, E., Mendoza,
 
 <!-- Motivation for the creation of this dataset. -->
 
+This dataset contains the majority of all known SMILES to flavor mappings publicly available. In order to use this data for supervised machine learning, both the SMILES and the flavor categories had to be made consistent. 
+
 [More Information Needed]
 
 ### Source Data
 
 <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
 
+All databases contained SMILES or SMILES data was obtained for the molecule from PubChem. The databases were previously curated dataset of tastants with three exceptions: Tas2R Agonists DB lists molecules which bind the human taste receptor; Scifinder was used to search for acidic molecules even if they had not been expressly tested for taste; some umami compounds were added manually from the literature. 
+
 #### Data Collection and Processing
 
 <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
 
-[More Information Needed]
+SMILES were canonicalized with RDKit
+Any rows with empty fields were removed. 
+PubChem properties were enriched after duplicates were removed based on "Canonicalized SMILES" and "Canonicalized Flavor".
+
+FlavorDB: FlavorDB has human generated labels (e.g. "honey", "sweet-like", "tangy") which then had to be mapped onto the 5 canonical flavor categories. 
+ChemTastesDB: Human-generated labels were again canonicalized into the 5 flavor categories. 
+PhytocompoundsDB: Human-generated labels were again canonicalized into the 5 flavor categories. 
+Tas2R Agonists DB: This dataset contains molecules which bind the human bitter receptor. All datapoints were hence labelled as "bitter". 
+Scifinder: A random subset of small molecules (< 500 Da) that are listed with a pKa between 2 and 7 which is a safe range for human tasting.
+Umami DB: A small dataset of known umami compounds was manually curated from the literature.
 
 #### Who are the source data producers?