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Leveraging food for better health through data-driven approaches

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Have you ever wondered why do we combine ingredients in our recipes the way we do? Or for that matter, could we find scientific ways for altering diet to improve health? Our data-driven investigations aimed at probing patterns in traditional Indian recipes, in response to the first question, have led us to the discovery of a novel food pairing phenomenon in Indian cuisine. Our studies have revealed ‘culinary fingerprints’ of regional cuisines and role of spice as the molecular fulcrum of Indian recipes. Such data-driven explorations of food are opening new avenues for development of divergent applications in the domains of nutrition and health. One such direction is towards application of machine learning for ‘personalized nutrition’ that can potentially answer the second question, allowing us to leverage food as medicine.

Published in: Health & Medicine
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Leveraging food for better health through data-driven approaches

  1. 1. Ganesh Bagler Center for Computational Biology, IIIT-Delhi http://faculty.iiitd.ac.in/~bagler bagler@iiitd.ac.in
  2. 2. Image Credits: Chloe Cushman
  3. 3. Image Credits: Chloe Cushman Genes Friends Physical activity Diet
  4. 4. Why do we eat what we eat? Why do we combine ingredients in our recipes the way we do?
  5. 5. Cuisines: Traditional Recipes A data and hypothesis oriented approach to food The Molecular Essence The quintessential molecular character Exploiting patterns for health Data-driven personalized food recommendation
  6. 6. 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0
  7. 7. :: Data :: well tested & well tasted
  8. 8. 2543 Traditional Indian Recipes (TarlaDalal) Regional cuisines: Bengali, Gujarati, Jain, Maharashtrian, Mughlai, Punjabi, Rajasthani, South Indian.
  9. 9. Why do we combine ingredients in our recipes the way we do?
  10. 10. Cuisines: Traditional Recipes A data and hypothesis oriented approach to food The Molecular Essence The quintessential molecular character Exploiting patterns for health Data-driven personalized food recommendation
  11. 11. Food Pairing Hypothesis Ingredients sharing flavor compounds are more likely to taste well together than ingredients that do not. 𝑁𝑠 = 𝐹𝑖 ∩ 𝐹𝑗 𝐹𝑖 𝐹𝑗 Ahn et. al, “Flavor network and the principles of food pairing”, 1, 196, Scientific Reports (2011). A Jain, NK Rakhi, G Bagler*, “Spices form the basis of food pairing in Indian cuisine”, arXiv:1502.03815 (2015).
  12. 12. fla•vor = aroma + taste olfactory gustatory
  13. 13. 194 ingredients 1170 flavor molecules Ahn et. al, Sci.Rep., 1, 196 (2011).
  14. 14. 𝑁𝑠 𝑅𝑎𝑛𝑑 𝑁𝑠 𝐶𝑢𝑖𝑠𝑖𝑛𝑒 𝑁𝑠 𝐶𝑢𝑖𝑠𝑖𝑛𝑒 ∆𝑁𝑠 ∆𝑁𝑠 Western Cuisines Ahn et. al, Sci.Rep. (2011) Indian Cuisine Jain et. al, PLoS ONE (2015) Uniform Food Pairing Contrasting Food Pairing Unique pairing in Indian cuisine
  15. 15. Indian cuisine is characterized with contrasting food pairing. more the extent of flavor sharing between any two ingredients, lesser their co-occurrence
  16. 16. Contrasting Food Pairing —at the level of ingredient pairs— A Jain, NK Rakhi, G Bagler*, “Spices form the basis of food pairing in Indian cuisine”, arXiv:1502.03815 (2015).
  17. 17. A Jain, NK Rakhi, G Bagler*, “Spices form the basis of food pairing in Indian cuisine”, arXiv:1502.03815 (2015). Contrasting Food Pairing —at the level of cuisine—
  18. 18. A Jain, NK Rakhi, G Bagler*, “Spices form the basis of food pairing in Indian cuisine”, arXiv:1502.03815 (2015). Contrasting Food Pairing —at the level of sub-cuisines—
  19. 19. Indian cuisine is characterized with contrasting food pairing. more the extent of flavor sharing between any two ingredients, lesser their co-occurrence
  20. 20. A Jain, NK Rakhi & G Bagler,* “Analysis of Food Pairing in Regional Cuisines of India”, PLoS ONE, 10(10): e0139539(2015). Culinary Fingerprinting of Regional Cuisines of India
  21. 21. A Jain, NK Rakhi, G Bagler*, “Spices form the basis of food pairing in Indian cuisine”, arXiv:1502.03815 (2015). Spices are key to the food pairing in Indian cuisine
  22. 22. Positive (Uniform)Negative (Contrasting) A Jain, NK Rakhi, G Bagler*, “Spices form the basis of food pairing in Indian cuisine”, arXiv:1502.03815 (2015). Role of ingredients in biasing the food pairing
  23. 23. Spice The Taste of India
  24. 24. Discovery of the molecular essence of Indian cuisine & applications Highlighted as an Emerging Technology in A Jain, NK Rakhi and G Bagler*, arXiv (2015); A Jain, NK Rakhi and G Bagler*, PLoS ONE (2015). Best of 2015 MIT Technology Review
  25. 25. Cuisines: Traditional Recipes A data and hypothesis oriented approach to food The Molecular Essence The quintessential molecular character Exploiting patterns for health Data-driven personalized food recommendation
  26. 26. Molecular Essence Novel Recipe Generation Food Formulations Food- Beverage pairing Hypothesis Generation & Testing Nutri- Genomics Food- Disease Association
  27. 27. Can we find scientific ways for altering diet to improve health? Personalized food recommendation
  28. 28. Levels of glucose in the blood are measured in terms of “Postprandial Glycemic Response (PPGR)”. Image Credits: HealthClinic
  29. 29. Machine learning applied to multidimensional data for personalized dietary recommendation ED Sonnenburg and JL Sonnenburg, Nature, 528, 484 (Dec 2015). Zeevi et al., “Personalized Nutrition by Prediction of Glycemic Responses”, Cell, 163, 1079-1094 (Nov 2015);
  30. 30. The discovery of a new dish confers more happiness on humanity, than the discovery of a new star. Jean Anthelme Brillat-Savarin “ ” as seen in IUCAA canteen circa 1998
  31. 31. Image Credits: Wikipedia, Google Images (wherever applicable)

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