Back

Estimation of Interaction and Growth Parameters to Develop a Computational Model for Gut Bacteria

Joshi, H.; Prakash, M. K.

2023-03-24 biophysics
10.1101/2023.03.22.533813 bioRxiv
Show abstract

The relevance of gut bacterial balance to human health can not be overemphasized. The gut bacterial balance delicately relies on several factors inherent to the person as well as to the environment. As the volume of evidences for the gut bacterial influence on health and the clinical data on the variance of the bacterial population across cohorts continue to grow exponentially, it is important to develop a theoretical model for gut bacteria. In this work, we suggest a new computational method for estimating the interaction parameters from the cross-sectional data of bacterial abundances in a cohort, without requiring a longitudinal followup. We introduce a nutrient type based bacterial growth model and use the Monte Carlo approach to estimate the matrix of interaction parameters for the 14 major bacterial species. These parameters were used in a comprehensive first-level computational model we developed for the large intestine to understand the patterns of re-establishing balance with different nutrient types.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.