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Informatics Approaches for Harmonized Intelligent Integration of Stem Cell Research

Authors Finkelstein J, Parvanova I, Zhang F

Received 5 November 2019

Accepted for publication 11 January 2020

Published 28 January 2020 Volume 2020:13 Pages 1—20

DOI https://doi.org/10.2147/SCCAA.S237361

Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 2

Editor who approved publication: Dr Bernard Binetruy


Joseph Finkelstein, 1 Irena Parvanova, 1 Frederick Zhang 2

1Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA; 2Center for Bioinformatics and Data Analytics, Columbia University, New York, NY, USA

Correspondence: Joseph Finkelstein
Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, Icahn L2-36, New York, NY 10029, USA
Tel +1 212-659-9596
Email Joseph.Finkelstein@mssm.edu

Abstract: As biomedical data integration and analytics play an increasing role in the field of stem cell research, it becomes important to develop ways to standardize, aggregate, and share data among researchers. For this reason, many databases have been developed in recent years in an attempt to systematically warehouse data from different stem cell projects and experiments at the same time. However, these databases vary widely in their implementation and structure. The aim of this scoping review is to characterize the main features of available stem cell databases in order to identify specifications useful for implementation in future stem cell databases. We conducted a scoping review of peer-reviewed literature and online resources to identify and review available stem cell databases. To identify the relevant databases, we performed a PubMed search using relevant MeSH terms followed by a web search for databases which may not have an associated journal article. In total, we identified 16 databases to include in this review. The data elements reported in these databases represented a broad spectrum of parameters from basic socio-demographic variables to various cells characteristics, cell surface markers expression, and clinical trial results. Three broad sets of functional features that provide utility for future stem cell research and facilitate bioinformatics workflows were identified. These features consisted of the following: common data elements, data visualization and analysis tools, and biomedical ontologies for data integration. Stem cell bioinformatics is a quickly evolving field that generates a growing number of heterogeneous data sets. Further progress in the stem cell research may be greatly facilitated by development of applications for intelligent stem cell data aggregation, sharing and collaboration process.

Keywords: stem cells, data integration, databases

Creative Commons License This work is published by Dove Medical Press Limited, and licensed under a Creative Commons Attribution License. The full terms of the License are available at http://creativecommons.org/licenses/by/4.0/. The license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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