Machine learning-based data analytic approaches for evaluating post-natal mouse respiratory physiological evolution.

ABSTRACT: Respiratory parameters change during post-natal development, but the nature of their changes have not been well-described. The advent of commercially available plethysmographic instruments provided improved repeatability of measurements and standardization of measured breathing in mice across laboratories. These technologies thus allowed for exploration of more precise respiratory pattern changes during the post-natal developmental epoch. Current methods to analyze respiratory behavior utilize plethysmography to acquire standing values of frequency, volume and flow at specific time points in murine maturation. These metrics have historically been independently analyzed as a function of time with no further analysis examining the interplay these variables have with each other and in the con

SUBMITTER: Wang W 

PROVIDER: S-EPMC7881416 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature