Spatial organization of proteomes: A low-rank approximation

TL;DR

This paper introduces a low-rank approximation method to analyze the spatial organization of proteomes, providing a numerical scheme for protein interaction networks and testing it on neuronal compartment datasets.

Contribution

It presents a novel low-rank approximation approach for understanding proteome spatial organization and offers a new numerical scheme for protein network analysis.

Findings

Effective in characterizing proteome spatial organization

Applicable to neuronal compartment datasets

Provides a new tool for protein interaction analysis

Abstract

We investigate the problem of signal transduction via a descriptive analysis of the spatial organization of the complement of proteins exerting a certain function within a cellular compartment. We propose a scheme to assign a numerical value to individual proteins in a protein interaction network by means of a simple optimization algorithm. We test our procedure against datasets focusing on the proteomes in the neurite and soma compartments.