PhenoMultiOmics: an enzymatic reaction inferred multi-omics network visualization web server.

Area of Science:

• Biochemistry
• Systems Biology
• Bioinformatics

Background:

• Enzymatic reactions are crucial for cellular processes and their disruption in disease necessitates visualization of multi-omics networks.
• Understanding these perturbed networks aids in comprehending biological system functionality and regulation.

Purpose of the Study:

• To design PhenoMultiOmics, a web server for exploring enzymatic reaction-based multi-omics networks in various cancer types.
• To enable visualization of gene, protein, and metabolite interplay influenced by cancer-related enzymatic reactions.

Main Methods:

• Curated a database of cancer-gene-protein-metabolite relationships linked by enzymatic reactions.
• Developed a multi-omics network visualization module and a biomarker discovery module.
• Applied the server to analyze transcriptomics data of gastric cancer and metabolomics data of lung cancer.

Main Results:

• PhenoMultiOmics provides a platform for exploring cancer multi-omics networks based on enzymatic reactions.
• The tool facilitates functional analysis via differential omic feature expression and pathway enrichment.
• Case studies on gastric and lung cancer yielded mechanistic insights into disrupted enzymatic reactions.

Conclusions:

• PhenoMultiOmics offers a valuable resource for researchers studying enzymatic reactions in cancer.
• The web server aids in understanding disease mechanisms and identifying potential biomarkers through multi-omics data integration.