TY - JOUR
T1 - A Parallel Discrete Artificial Bee Colony Framework for Inferring Causal Protein Signalling Networks from Single-Cell Data
AU - Luca Ferraro
AU - Matteo Ricci
AU - Giulia Moretti
AU - Paolo Greco
JF - Journal of Trustworthy and Explainable Intelligent Systems
JO - J Trustworthy Explain Intell Syst
Y1 - 2023
VL - 2
IS - 1
SP - 30
N2 - Deducing causal protein signalling networks using human immune system cellular data offers a encouraging pathway to decode both fundamental tissue signaling biology and the underlying abnormalities in pathological cells. Consequently, this domain has drawn substantial interest within bioinformatics. More recently, Bayesian network (BN) approaches have become highly prominent for reconstructing causal protein signalling pathways from high-dimensional single-cell datasets. Nevertheless, existing BN algorithms frequently suffer from elevated computational demands and overlook the interplay among signaling molecules across distinct single cells. To address these issues, this paper introduces a novel score-based BN framework named parallel discrete artificial bee colony (PDABC) for uncovering causal protein signalling architectures. Specifically, PDABC leverages a parallelized artificial bee colony framework to explore the search space and identify the globally optimal network topology maximizing the discrete K2 score metric. Performance assessments conducted on multiple synthetic benchmarks, alongside a public multi-parameter fluorescence-activated cell sorter dataset, demonstrate that the proposed PDABC framework exceeds contemporary state-of-the-art techniques regarding both structural accuracy and computational throughput.
UR - https://tipublications.com/m918482844
ER -