Back to search

Article

Transcriptome-driven Health-status Transversal-predictor Analysis (THTA) using the PBMC transcriptome for health, food, microbiome and disease markers for understanding the background and development of lifestyle diseases

2024-10-24

Abstract excerpt

We developed a novel machine-learning artificial intelligence (AI) approach to predict general health and food-intake parameters named Transcriptome-driven Health-status Transversal-predictor Analysis (THTA) with relevance for diabesity markers based on a mathematics-driven and non-transcriptomic biomarker driven approach. The prediction was based on values from food consumption, dietary lipids and their bioactive...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
8153c806-29a7-5286-b4c5-936da5b2af48
DOI
10.1101/2024.10.24.24316039
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Transcriptome-driven Health-status Transversal-predictor Analysis (THTA) using the PBMC transcriptome for health, food, microbiome and disease markers for understanding the background and development of lifestyle diseasesDOI 10.1101/2024.10.24.24316039
Select a neighboring publication to make it the new centre.