Single-Cell Data Science (SCDS)

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Informatics and Big Data".

Deadline for manuscript submissions: closed (15 September 2022) | Viewed by 7600

Special Issue Editor

Departments of Melanoma Medical Oncology and Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
Interests: computational cancer genomics; next generation sequencing; targeted therapy; immunotherapy; target discovery; drug repurposing; rare cancers
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues,

Single-cell sequencing technologies have greatly enhanced our ability to characterize heterogeneous tumor and normal cell populations to understand biological processes and identify novel therapeutic targets. Computational tools have been developed in recent years; however, analysis of single-cell sequencing data remains challenging and time-consuming, especially when integrating multiple types of data. This Special Issue of Cancers is devoted to papers and reviews on the latest advances and unprecedented opportunities in single-cell data science. We invite manuscripts from authors who are interested in developing novel tools, methods, and resources, as well as those who have new insights and applications to share in this area.

Dr. Jason Roszik
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. Cancers is an international peer-reviewed open access semimonthly 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 2900 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 sequencing
  • scRNA-seq
  • cellular heterogeneity
  • statistical methods
  • benchmarking studies
  • data visualization
  • single-cell atlases

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Editorial

Jump to: Review

2 pages, 151 KiB  
Editorial
Opportunities for Single-Cell Sequencing Technologies and Data Science
by Lisa Maria Mustachio and Jason Roszik
Cancers 2020, 12(11), 3433; https://doi.org/10.3390/cancers12113433 - 19 Nov 2020
Cited by 1 | Viewed by 1249
Abstract
This Special Issue on “Single-cell Data Science” aims to highlight recent advances in the area of single-cell sequencing technologies and data analytics [...] Full article
(This article belongs to the Special Issue Single-Cell Data Science (SCDS))

Review

Jump to: Editorial

10 pages, 607 KiB  
Review
Single-Cell Sequencing: Current Applications in Precision Onco-Genomics and Cancer Therapeutics
by Lisa Maria Mustachio and Jason Roszik
Cancers 2022, 14(3), 657; https://doi.org/10.3390/cancers14030657 - 28 Jan 2022
Cited by 8 | Viewed by 5324
Abstract
Single-cell sequencing encompasses a variety of technologies that evaluate cells at the genomic, transcriptomic, epigenomic, and proteomic levels. Each of these levels can be split into additional techniques that enable specific and optimized sequencing for a specialized purpose. At the transcriptomic level, single-cell [...] Read more.
Single-cell sequencing encompasses a variety of technologies that evaluate cells at the genomic, transcriptomic, epigenomic, and proteomic levels. Each of these levels can be split into additional techniques that enable specific and optimized sequencing for a specialized purpose. At the transcriptomic level, single-cell sequencing has been used to understand immune-malignant cell networks, as well as differences between primary versus metastatic tumors. At the genomic and epigenomic levels, single-cell sequencing technology has been used to study genetic mutations involved in tumor evolution or the reprogramming of regulatory elements present in metastasized disease, respectively. Lastly, at the proteomic level, single-cell sequencing has been used to identify biomarkers important for predicting patient prognosis, as well as biomarkers essential for evaluating optimal treatment strategies. Integrated databases and atlases, as a result of large sequencing experiments, provide a vast array of information that can be applied to various studies and accessed by researchers to further answer scientific questions. This review summarizes recent, high-impact literature covering these aspects, as well as single-cell sequencing in the translational setting. Specifically, we review the potential that single-cell sequencing has in the clinic and its implementation in current clinical studies. Full article
(This article belongs to the Special Issue Single-Cell Data Science (SCDS))
Show Figures

Figure 1

Back to TopTop