2023
Temporary and Permanent Control of Partially Specified Boolean Networks
BRIM, Luboš; Samuel PASTVA; David ŠAFRÁNEK a Eva ŠMIJÁKOVÁZákladní údaje
Originální název
Temporary and Permanent Control of Partially Specified Boolean Networks
Autoři
Vydání
BIOSYSTEMS, Elsevier, 2023, 0303-2647
Další údaje
Jazyk
angličtina
Typ výsledku
Článek v odborném periodiku
Obor
10201 Computer sciences, information science, bioinformatics
Stát vydavatele
Irsko
Utajení
není předmětem státního či obchodního tajemství
Odkazy
Impakt faktor
Impact factor: 2.000
Kód RIV
RIV/00216224:14330/23:00130043
Organizační jednotka
Fakulta informatiky
UT WoS
000890559900005
EID Scopus
2-s2.0-85141496190
Klíčová slova anglicky
Boolean network; Perturbation; Temporary Control; Permanent Control; Symbolic Algorithm
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 8. 4. 2024 15:35, RNDr. Pavel Šmerk, Ph.D.
Anotace
V originále
Boolean networks (BNs) are a well-accepted modelling formalism in computational systems biology. Neverthe-less, modellers often cannot identify only a single BN that matches the biological reality. The typical reasons for this is insufficient knowledge or a lack of experimental data. Formally, this uncertainty can be expressed using partially specified Boolean networks (PSBNs), which encode the wide range of network candidates into a single structure. In this paper, we target the control of PSBNs. The goal of BN control is to find perturbations which guarantee stabilisation of the system in the desired state. Specifically, we consider variable perturbations (gene knock-out and over-expression) with three types of application time-window: one-step, temporary, and permanent. While the control of fully specified BNs is a thoroughly explored topic, control of PSBNs introduces additional challenges that we address in this paper. In particular, the unspecified components of the model cause a significant amount of additional state space explosion. To address this issue, we propose a fully symbolic methodology that can represent the numerous system variants in a compact form. In fully specified models, the efficiency of a perturbation is characterised by the count of perturbed variables (the perturbation size). However, in the case of a PSBN, a perturbation might work only for a subset of concrete BN models. To that end, we introduce and quantify perturbation robustness. This metric characterises how efficient the given perturbation is with respect to the model uncertainty. Finally, we evaluate the novel control methods using non-trivial real-world PSBN models. We inspect the method's scalability and efficiency with respect to the size of the state space and the number of unspecified components. We also compare the robustness metrics for all three perturbation types. Our experiments support the hypothesis that one-step perturbations are significantly less robust than temporary and permanent ones.
Návaznosti
| GA22-10845S, projekt VaV |
| ||
| MUNI/A/1081/2022, interní kód MU |
|