DietRx provides a platform for exploring health impacts of dietary ingredients by integrating interrelationships among food and key molecular agents. The resource assimilates dietary factors (food and chemicals), their health consequences (diseases) and genetic mechanisms to facilitate queries for investigating associations among these entities

DietRx comprises of four entities: Food, Disease, Chemical and Gene. The resource integrates evidence of associations among these entities and facilitates in drawing inferences relating them.

DIetRx facilitates an elastic search to query food, disease, chemical and gene. Each of these could be flexibly queried using standard/scientific/common symbols/names. The search results page for each of these entities provides all relevant associations with the remaining entities (if available), and the tables themselves are searchable.

DietRx includes data of 2337 foods belonging to 25 food categories (plant, fruit, meat etc.).

DietRx includes data of 6992 chemicals from 2337 foods and were compiled from KNApSAcK, PhenolExlorer, USDA, DUKE, and FooDB.

DietRx includes data of 20550 genes.

DietRx uses the MEDIC disease vocabulary from CTD (The Comparative Toxicogenomics Database). MEDIC is a modified subset of U.S. National Library of Medicine's MeSH® (Medical Subject Headings) terms present under the "Disease" [C] branch, combined with genetic disorders from the OMIM® (Online Mendelian Inheritance in Man®) database.

DietRx uses the MEDIC-Slim categorization of diseases, under which a MEDIC disease can belong to multiple Slim categories. More info can be found here.

The data of food-disease associations was text-mined from biomedical literature. Food-chemical associations were curated from KNApSAcK, PhenolExlorer, USDA, DUKE, and FooDB. Disease-Chemical and Chemical-Gene associations were curated from CTD (The Comparative Toxicogenomics Database). Disease-Gene associations were obtained through DisGeNET. Further, we used one-hop-relations to infer associations between the entities.

An entity 'A' may be linked to another entity 'B' directly or through some other entity 'C'. Inferring associations between 'A' and 'B' involves traversing the association path from 'A' to 'C' and from 'C' to 'B'.

For example: Food-Gene associations may be inferred via 'Disease Terms' or via 'Chemicals'. The former refers to an indirect association in which the food is reported to be associated with a disease term which is further linked with the gene. And the latter refers to inferred association in which a chemical reported to be found in the food is linked with the gene.

Positive food-disease associations refer to the beneficial effects whereas negative food-disease associations refer to the adverse effects of the food against the disease. These associations were obtained through the text mining protocol involving Named Entity Recognition for food and disease entities from the corpus of biomedical literature and machine learning models built by training manually annotated data.

Therapeutic associations between chemical-disease refer to the beneficial effects of the chemical against the disease, whereas marker/mechanism associations refer to situations where it's unknown whether the effects of the chemical are beneficial or adverse.

DietRx facilitates an elastic search to query food, disease, chemical and gene. The search algorithm is flexible enough to allow for minor variations in spelling while retrieving the most appropriate results.

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All material on this website is a product of research and is provided for your information only and may not be construed as medical advice or instruction. No action or inaction should be taken based solely on the contents of this information; instead, readers should consult appropriate health professionals on any matter relating to their health and well-being.

Name	Position	Affiliation	Contribution
Ganesh Bagler	Project Head	Center for Computational Biology, Indraprastha Institute of Information Technology (IIIT-Delhi), New Delhi	Idea conception, Project design and management, Database design and implementation
Rudraksh Tuwani	Research Assistant	Center for Computational Biology, Indraprastha Institute of Information Technology	Data Curation, Database design, Development of DietRx Web Resource, Data Visualisation and Data Analytics
Neelansh Garg	Summer Research Intern	Center for Computational Biology, Indraprastha Institute of Information Technology	Database design, Development of DietRx Web Resource
Rakhi N K	PhD Research Scholar	Department of Bioscience and Bioengineering, Indian Institute of Technology Jodhpur, Jodhpur	Manual data compilation, Annotation and curation, Quality Check, Analysis
Rujhil Jain	M.Tech	Department of Computer Science And Engineering, IIIT-Delhi, Delhi	Contributed to backend development, database enhancements, and system optimization
Sneha Nandi	M.Tech	Department of Computer Science And Engineering, IIIT-Delhi, Delhi	Focused on data handling, backend consistency, and performance improvements
Shriyansh Bhardwaj	M.Tech	Department of Computer Science And Engineering, IIIT-Delhi, Delhi	Enhanced the user interface, optimized web functionalities, and supported system integration

Rudraksh Tuwani†, Neelansh Garg†, Rakhi NK, Rujhil Jain, Sneha Nandi, Shriyansh Bhardwaj and Ganesh Bagler*, DietRx: An integrative resource to explore interrelationships among foods, diseases, genes and chemicals (2025), http://cosylab.iiitd.edu.in/dietrx/.

†Equal contribution *Corresponding Author