ArticleJournal of biosciences2022
Computational gastronomy: A data science approach to food.
Article in Journal of biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 4 citations in OpenAlex.
- From Cookbooks to Networks: A Framework for Comparing Multiethnic Ingredient Systems in Transylvania.Foods (Basel, Switzerland) · 2026Article
- The networks of ingredient combinations as culinary fingerprints of world cuisines.NPJ science of food · 2025Article
- The recipe similarity network: a new algorithm to extract relevant information from cookbooks.Scientific reports · 2025Article
- Trends and Directions of Preference Elicitation and Assessment in Food Science: Single-, Pair-, and Multi-Criteria Ranking Methods.Food science & nutrition · 2025Review
- Decoding Global Palates: Unveiling Cross-Cultural Flavor Preferences Through Online Recipes.Foods (Basel, Switzerland) · 2025Article
- Gastronomic paradigm shifts revisited: from culinary abstraction to a post-digital integrative cuisine.Frontiers in nutrition · 2025Article
- Computational gastronomy: capturing culinary creativity by making food computable.NPJ systems biology and applications · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cooking forms the core of our cultural identity other than being the basis of nutrition and health. The increasing availability of culinary data and the advent of computational methods for their scrutiny are dramatically changing the artistic outlook towards gastronomy. Starting with a seemingly simple question, 'Why do we eat what we eat?', data-driven research conducted in our lab has led to interesting explorations of traditional recipes, their flavor composition, and health associations. Our investigations have revealed 'culinary fingerprints' of regional cuisines across the world. Application of data-driven strategies for investigating the gastronomic data has opened up exciting avenues, giving rise to an all-new field of 'computational gastronomy'. This emerging interdisciplinary science asks questions of culinary origin to seek their answers via the compilation of culinary data and their analysis using methods of complex systems, statistics, computer science, and artificial intelligence. Along with complementary experimental studies, these endeavors have the potential to transform the food landscape by effectively leveraging data-driven food innovations for better health and nutrition.
Indexed as
Identifiers
35092414W4225822664What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.