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ORCO: Ollivier-Ricci Curvature-Omics - an unsupervised method for analyzing robustness in biological systems.

Authors :
Simhal AK
Weistuch C
Murgas K
Grange D
Zhu J
Oh JH
Elkin R
Deasy JO
Source :
BioRxiv : the preprint server for biology [bioRxiv] 2024 Oct 11. Date of Electronic Publication: 2024 Oct 11.
Publication Year :
2024

Abstract

Although recent advanced sequencing technologies have improved the resolution of genomic and proteomic data to better characterize molecular phenotypes, efficient computational tools to analyze and interpret the large-scale omic data are still needed. To address this, we have developed a network-based bioinformatic tool called Ollivier-Ricci curvature-omics (ORCO). ORCO incorporates gene interaction information with omic data into a biological network, and computes Ollivier-Ricci curvature (ORC) values for individual interactions. ORC, an edge-based measure, indicates network robustness and captures global gene signaling changes in functional cooperation using a consistent information passing measure, thereby helping identify therapeutic targets and regulatory modules in biological systems. This tool can be applicable to any data that can be represented as a network. ORCO is an open-source Python package and publicly available on GitHub at https://github.com/aksimhal/ORC-Omics.

Details

Language :
English
ISSN :
2692-8205
Database :
MEDLINE
Journal :
BioRxiv : the preprint server for biology
Publication Type :
Academic Journal
Accession number :
39416154
Full Text :
https://doi.org/10.1101/2024.10.06.616915