Clustering analysis of tumor metabolic networks.

ABSTRACT:

Background

Biological networks are representative of the diverse molecular interactions that occur within cells. Some of the commonly studied biological networks are modeled through protein-protein interactions, gene regulatory, and metabolic pathways. Among these, metabolic networks are probably the most studied, as they directly influence all physiological processes. Exploration of biochemical pathways using multigraph representation is important in understanding complex regulatory mechanisms. Feature extraction and clustering of these networks enable grouping of samples obtained from different biological specimens. Clustering techniques separate networks depending on their mutual similarity.

Results

We present a clustering analysis on tissue-specific metabolic networks fo

SUBMITTER: Manipur I 

PROVIDER: S-EPMC7446216 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature