2026-08-27T21:19:51Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:27530 2026-08-27T06:04:08Z ddc:004 open_access

FBApro: A Fast, Simple Linear Transformation for Diverse Metabolic Modeling Tasks Bruner, Ariel Singh, Mona metabolic modeling flux balance analysis constraint-based metabolic modeling Constraint-based metabolic modeling is the predominant framework for simulating cellular metabolism. The central assumption of these models is that metabolism operates at a steady state, meaning that the production and consumption rates of each metabolite are balanced. This assumption imposes linear constraints on the fluxes of biochemical reactions. Flux Balance Analysis (FBA), a fundamental method in the field, is formulated as an optimization problem maximizing a cellular objective (e.g., growth) over the resulting linear subspace of steady state fluxes. Many other methods in the field are expressed either as a modification to FBA, or use FBA as a black box within an algorithm. Here, we propose a general alternative to optimization called FBApro. For any given vector of reference fluxes, FBApro finds the closest flux vector within the steady-state subspace, and accounts for both partially given reference fluxes and exact constraints on reactions. While FBApro is the solution to a quadratic program, we show that it can be implemented as a single linear operation using orthogonal projections to corresponding affine spaces and sets of linear equations. The overall approach is computationally efficient, does not require a cellular objective, and is easy to implement. We formally derive the closed-form expressions for FBApro and simpler variants, and validate it on both synthetic and real cancer cell line data. Code availability. The code implementing FBApro is available at https://github.com/Singh-Lab/FBApro. All code required to reproduce the figures in the paper is available, although the data used must be sourced separately. The repository also contains toy models and examples. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Ariel Bruner and Mona Singh 2026 Is Part Of LIPIcs, Volume 390, 26th International Conference on Algorithms for Bioinformatics (WABI 2026) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.WABI.2026.26 urn:nbn:de:0030-drops-275305 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2026.26 eng https://creativecommons.org/licenses/by/4.0/legalcode