Nutritive Knowledge Based Discovery: Enhancing Precision Nutrition Hypothesis Generation

1 online resource (115 pages) : PDF

2022

University of North Carolina at Charlotte

Diet-related diseases like obesity and type-2 diabetes are on the rise. Precision nutrition, a way to tailor dietary requirements for each individual, is heralded as a solution to these problems. However, nutritional research is held within sparse, siloed resources that rarely connect, which leads to significant barriers hindering the progress of precision nutrition. Three knowledgebases were produced as a result of this work. The ABCkb 1.0 overcomes these barriers by linking 11 separate resources in the path from plants to disease through molecular mechanisms. This resource is built in Neo4j and provides a web-based interface available for browsing (https://abckb.charlotte.edu). A second knowledgebase, ABCkb 2.0 connects micro- biota information to diet and human health through the incorporation of text-mined associations from full text articles. The final knowledgebase produced links long-covid to dietary components through possible molecular mechanisms. These three knowledgebases promote progress in precision nutrition to tackle the rise in diet-related disease.

doctoral dissertations

Bioinformatics
Nutrition
Information science

Ph.D.

Human Health
Information
Knowledgebase
Natural Language Processing
Nutrition
Text-Mining

Bioinformatics

Brouwer, Cory

Reid, Robert
Gibas, Cynthia
Sung, Way
Newton, Xiaoxia

Thesis (Ph.D.)--University of North Carolina at Charlotte, 2022.

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Trautman_uncc_0694D_13058

http://hdl.handle.net/20.500.13093/etd:3002