Hybrid Metabolic Network Completion

TL;DR

This paper presents a hybrid approach combining qualitative and quantitative methods to improve metabolic network completion, effectively restoring highly degraded networks by integrating ASP with reaction rate constraints.

Contribution

It introduces a formal unified framework and a hybrid ASP encoding that incorporates reaction rates, advancing beyond previous qualitative-only methods.

Findings

Superior results on E. coli network completion

Effective restoration of highly degraded networks

Integration of qualitative and quantitative approaches

Abstract

Metabolic networks play a crucial role in biology since they capture all chemical reactions in an organism. While there are networks of high quality for many model organisms, networks for less studied organisms are often of poor quality and suffer from incompleteness. To this end, we introduced in previous work an ASP-based approach to metabolic network completion. Although this qualitative approach allows for restoring moderately degraded networks, it fails to restore highly degraded ones. This is because it ignores quantitative constraints capturing reaction rates. To address this problem, we propose a hybrid approach to metabolic network completion that integrates our qualitative ASP approach with quantitative means for capturing reaction rates. We begin by formally reconciling existing stoichiometric and topological approaches to network completion in a unified formalism. With it, we develop a hybrid ASP encoding and rely upon the theory reasoning capacities of the ASP system clingo for solving the resulting logic program with linear constraints over reals. We empirically evaluate our approach by means of the metabolic network of Escherichia coli. Our analysis shows that our novel approach yields greatly superior results than obtainable from purely qualitative or quantitative approaches. Under consideration in Theory and Practice of Logic Programming (TPLP).