Use of Single-Cell Omics in Personalized Medicine

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Omics/Informatics".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 2028

Special Issue Editor


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Guest Editor
1. Director NEXUS Personalized Health Technologies, Head Clinical Bioinformatics, ETH Zurich, Zurich, Switzerland
2. SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
Interests: bioinformatics; gene expression; proteomics; statistics; statistical data analysis; personalized health

Special Issue Information

Dear Colleagues,

Single-cell measurements are becoming the next mainstay of biomedical research projects. We still rely heavily on the sequencing of constitutional DNA and bulk RNA, but the additional resolution of observing cells as individual entities allows us to address countless new and interesting questions. While addressing fundamental research questions at single-cell resolution is becoming increasingly common, the translation of single-cell omics to the clinical setting is still rare. However, this is not equally true for all modalities. The use of CyTOF to simultaneously quantify concentrations of multiple cellular features has entered the diagnostic process in clinics, at least for certain diseases.

Especially in the domain of oncology, single-cell omics has shown its usefulness by enabling physicians to assess (among others) immune infiltration through image-based technologies, the clonality of tumors through single-cell RNA and DNA sequencing, and cell-type-specific drug response through empiric drug testing.

That being said, there is still a great deal of work to be done to make single-cell technologies go-to tools in personalized medicine. Therefore, we invite you to submit your research to this Special Issue. 

This Special Issue aims to give an overview of the applicability of single-cell omics in the medical setting: which methods can work in which technology and truly personalize the treatment decision process of physicians for a more beneficial patient outcome. We welcome original research articles, case reports, and reviews. Research areas may include (but are not limited to) clinical bioinformatics, digital pathology, computational biology, and translational medicine.

Dr. Daniel J. Stekhoven
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Personalized Medicine is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • single cell
  • biomarkers
  • microenvironment
  • translation
  • bioinformatics

Published Papers (1 paper)

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Research

13 pages, 3663 KiB  
Article
Analysis of MicroRNA Regulation and Gene Expression Variability in Single Cell Data
by Wendao Liu and Noam Shomron
J. Pers. Med. 2022, 12(10), 1750; https://doi.org/10.3390/jpm12101750 - 21 Oct 2022
Viewed by 1553
Abstract
MicroRNAs (miRNAs) regulate gene expression by binding to mRNAs, and thus reduce target gene expression levels and expression variability, also known as ‘noise’. Single-cell RNA sequencing (scRNA-seq) technology has been used to study miRNA and mRNA expression in single cells. To evaluate scRNA-seq [...] Read more.
MicroRNAs (miRNAs) regulate gene expression by binding to mRNAs, and thus reduce target gene expression levels and expression variability, also known as ‘noise’. Single-cell RNA sequencing (scRNA-seq) technology has been used to study miRNA and mRNA expression in single cells. To evaluate scRNA-seq as a tool for investigating miRNA regulation, we analyzed datasets with both mRNA and miRNA expression in single-cell format. We found that miRNAs slightly reduce the expression noise of target genes; however, this effect is easily masked by strong technical noise from scRNA-seq. We suggest improvements aimed at reducing technical noise, which can be implemented in experimental design and computational analysis prior to running scRNA-seq. Our study provides useful guidelines for experiments that evaluate the effect of miRNAs on mRNA expression from scRNA-seq. Full article
(This article belongs to the Special Issue Use of Single-Cell Omics in Personalized Medicine)
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