Single-Cell and Spatial Multi-Omics Technologies in Human Health
A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Bioinformatics and Systems Biology".
Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 8715
Special Issue Editors
Interests: single-cell multi-omics; computational systems biology; deep learning; immuno-oncology microbiome; drug resistance
Interests: single-cell and spatial multi-omics; graph neural network; gene regulatory mechanism; immuno-informatics; senescent cells
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent advances in single-cell and spatial-sequencing technologies have enabled the characterization of cellular- and tissue-level heterogeneity and biological processes in complex diseases. This provides unprecedented opportunities to understand disease pathology at the single-cell level to find new diagnostic markers or new therapeutic targets. The analyses of single-cell and spatially resolved sequencing data allow mechanistic classification and development, providing a practical basis for improving the diagnosis and treatment of diseases.
In this Special Issue, we invite you to share computational methods and laboratory innovations that enable the concurrent and integrative analyses of single-cell and spatially resolved multi-omics data. We embrace any novel statistical or deep-learning-based tools, pipelines, and databases that are developed for conquering computational challenges and linking with human health using relevant data. We would also like to showcase novel findings as a result of applications of multi-omics to address significant questions related to human health, including, but not limited to, immuno-oncology, Alzheimer’s disease, host–microbiome interactions, aging, drug resistance, cancer diagnosis, etc. Original research, databases/webservers, and review papers are welcome.
We look forward to reading your contributions to this rapidly advancing, interdisciplinary field.
Dr. Anjun Ma
Prof. Dr. Qin Ma
Guest Editors
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Keywords
- single-cell multi-omics
- spatial multi-omics
- bioinformatics and biomedical informatics
- human health
- deep-learning methods
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