LogBTF: gene regulatory network inference using Boolean threshold network model from single-cell gene expression data.

Bibliographic Details
Title:	LogBTF: gene regulatory network inference using Boolean threshold network model from single-cell gene expression data.
Authors:	Li L; Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan 250061, China.; Advanced Modeling and Applied Computing Laboratory, Department of Mathematics, The University of Hong Kong, Hong Kong, China., Sun L; Advanced Modeling and Applied Computing Laboratory, Department of Mathematics, The University of Hong Kong, Hong Kong, China., Chen G; Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan 250061, China., Wong CW; Advanced Modeling and Applied Computing Laboratory, Department of Mathematics, The University of Hong Kong, Hong Kong, China., Ching WK; Advanced Modeling and Applied Computing Laboratory, Department of Mathematics, The University of Hong Kong, Hong Kong, China., Liu ZP; Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan 250061, China.
Source:	Bioinformatics (Oxford, England) [Bioinformatics] 2023 May 04; Vol. 39 (5).
Publication Type:	Journal Article; Research Support, Non-U.S. Gov't
Journal Info:	Publisher: Oxford University Press Country of Publication: England NLM ID: 9808944 Publication Model: Print Cited Medium: Internet ISSN: 1367-4811 (Electronic) Linking ISSN: 13674803 NLM ISO Abbreviation: Bioinformatics Subsets: MEDLINE
Database:	MEDLINE Complete
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Description
ISSN:	1367-4811
DOI:	10.1093/bioinformatics/btad256