Integration of single-cell multi-omics for gene regulatory network inference
| Autor: | Ricky Wai Tak Leung, Yaohua Hu, Jing Qin, Xinlin Hu, Fanjie Wu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
lcsh:Biotechnology
Sequencing data Biophysics Gene regulatory network Review Article Computational biology Biochemistry Genome Data type Single-cell multi-omics integration 03 medical and health sciences 0302 clinical medicine Gene regulatory network inference Structural Biology lcsh:TP248.13-248.65 Genetics ComputingMethodologies_COMPUTERGRAPHICS 030304 developmental biology 0303 health sciences Epigenome Computer Science Applications Single cell sequencing Single-cell sequencing 030220 oncology & carcinogenesis Multi omics Biotechnology |
| Zdroj: | Computational and Structural Biotechnology Journal, Vol 18, Iss, Pp 1925-1938 (2020) Computational and Structural Biotechnology Journal |
| ISSN: | 2001-0370 |
| Popis: | Graphical abstract The advancement of single-cell sequencing technology in recent years has provided an opportunity to reconstruct gene regulatory networks (GRNs) with the data from thousands of single cells in one sample. This uncovers regulatory interactions in cells and speeds up the discoveries of regulatory mechanisms in diseases and biological processes. Therefore, more methods have been proposed to reconstruct GRNs using single-cell sequencing data. In this review, we introduce technologies for sequencing single-cell genome, transcriptome, and epigenome. At the same time, we present an overview of current GRN reconstruction strategies utilizing different single-cell sequencing data. Bioinformatics tools were grouped by their input data type and mathematical principles for reader's convenience, and the fundamental mathematics inherent in each group will be discussed. Furthermore, the adaptabilities and limitations of these different methods will also be summarized and compared, with the hope to facilitate researchers recognizing the most suitable tools for them. |
| Databáze: | OpenAIRE |
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