LogicGep: Boolean networks inference using symbolic regression from time-series transcriptomic profiling data

Abstract Reconstructing the topology of gene regulatory network from gene expression data has been extensively studied. With the abundance functional transcriptomic data available, it is now feasible to systematically decipher regulatory interaction dynamics in a logic form such as a Boolean network...

Full description

Saved in:

Bibliographic Details
Published in:	Briefings in bioinformatics Vol. 25; no. 4
Main Authors:	Zhang, Dezhen, Gao, Shuhua, Liu, Zhi-Ping, Gao, Rui
Format:	Journal Article
Language:	English
Published:	England Oxford University Press 23.05.2024 Oxford Publishing Limited (England)
Subjects:	Algorithms Boolean Boolean algebra Boolean functions Computational Biology - methods Dynamic characteristics Functionals Gene expression Gene Expression Profiling - methods Gene Regulatory Networks Humans Inference Multiple objective analysis Network topologies Neural networks Neural Networks, Computer Problem Solving Protocol Software Structure-function relationships Time series Topology Topology optimization Transcriptome Transcriptomics single-cell RNA sequencing network inference Boolean network symbolic regression gene regulatory network
ISSN:	1467-5463, 1477-4054, 1477-4054
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!