Systems Biology of Single Cells: Bridging Genomics and Functional Insights
A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Bioinformatics".
Deadline for manuscript submissions: 15 June 2026 | Viewed by 1543
Special Issue Editor
Interests: bioinformatics; cytogenomics; systems biology; evolutionary biology; celular stressors
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Systems biology is a fruitful field focused on studying biological systems from a holistic rather than a reductionist perspective. This means that this area allows researchers to find, study, and describe the emergent properties of biological systems, which is not possible under reductionist views. This field provides unprecedented knowledge in many areas, including molecular and cell biology. In these cases, we have observed that the molecular mechanisms driving biological processes are much more intricate than previously thought. Single-cell RNA-Seq (scRNA-Seq) is a field in which scientists can analyze gene expression at the single-cell level. Overall, this approach is showing us that the complexity of expression in tissues is much more diverse and complex than previously thought. ScRNA-Seq evolved to study the cell-gene expression in situ, that is, in tissue samples, a technique called spatial transcriptomics. More recently, systems biology, scRNA-Seq, and spatial transcriptomics have been merged, allowing for astonishing discoveries concerning how each cell system behaves. Given the complexity of analyzing biological systems, new tools, approaches, concepts, and strategies focusing on systems biology, particularly in the context of single-cell RNA sequencing (scRNA-Seq) and spatial transcriptomes, have been emerging. Therefore, the authors are encouraged to submit original manuscripts concerning systems biology studies in scRNA-Seq and spatial transcriptomics. In this case, manuscripts describing new methods, approaches, ideas, or utilizing systems biology and graph theory to analyze these data in any field are welcome. Reviews and data reanalysis focusing on these themes will also be considered. Note that robust bioinformatics research should integrate both computational analyses and experimental biological validation.
Dr. Guilherme Targino Valente
Guest Editor
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Keywords
- systems biology
- graph theory
- single-cell RNA-Seq
- spatial transcriptomics
- molecular networks
- complex networks
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