Visualizing metabolic network dynamics through time-series metabolomic data.

ABSTRACT:

Background

New technologies have given rise to an abundance of -omics data, particularly metabolomic data. The scale of these data introduces new challenges for the interpretation and extraction of knowledge, requiring the development of innovative computational visualization methodologies. Here, we present GEM-Vis, an original method for the visualization of time-course metabolomic data within the context of metabolic network maps. We demonstrate the utility of the GEM-Vis method by examining previously published data for two cellular systems-the human platelet and erythrocyte under cold storage for use in transfusion medicine.

Results

The results comprise two animated videos that allow for new insights into the metabolic state of both cell types. In the case study of the p

SUBMITTER: Buchweitz LF 

PROVIDER: S-EPMC7119163 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature