Complexity, Information and Quantitative Modelling in Single Cell Multiomics
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Entropy and Biology".
Deadline for manuscript submissions: 28 February 2025 | Viewed by 161
Special Issue Editor
Special Issue Information
Dear Colleagues,
Single-cell omics technologies are now ubiquitous and provide high resolution in time and space on complex biological processes at the level of individual cells. Yet, this poses novel theoretical and computational challenges in translating high-throughput multimodal data into intelligible biological mechanisms and quantitative, falsifiable predictions. In this Special Issue, we encourage the submission of novel theoretical and computational approaches to advance the interpretability and model-generating potential of single-cell data. The proposed approaches can focus on any biological process (i.e., transcription, gene regulation, cell–cell interactions, cell lineage, etc.) and can be based on any modeling framework (i.e., information theory, stochastic modeling, machine learning, etc.) as long as the connection with single-cell methodologies is clear and justified. Examples of topics include the following:
- Theoretical and computational advancements to improve the interpretability and model generation from single-cell omics and/or multiomics data.
- Implementation of methodologies from various disciplines including but not limited to mathematics, statistics, machine learning, and biophysics to answer specific questions in single-cell biology.
- Application of new or existing modeling strategies to connect two or more single-cell data modalities (such as, but not limited to genomics, epigenomics, transcriptomics, proteomics, or metabolomics) and provide new biological insight.
- Finally, we allow the submission of review articles. The review article, however, should provide a perspective on current challenges and propose novel directions for the field, rather than solely summarize the literature.
Dr. Federico Bocci
Guest Editor
Manuscript Submission Information
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Keywords
- single-cell multi-omics
- theoretical modeling
- computational biology
- cell modeling
- information theory
- machine learning
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Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Authors: Zhenyi Zhang, Yuhao Sun, Qiangwei Peng, Tiejun Li, Peijie Zhou
Affiliation: Peking University, Beijing, China
