- Functional Virtual Flow Cytometry: A Visual Analytic Approach for Characterizing Single-Cell Gene Expression Patterns, Zhi Han, Travis Johnson, Jie Zhang, Xuan Zhang, and Kun Huang
BioMed Research International
Research Article (9 pages), Article ID 3035481, Volume 2017 (2017)
Published 17 July 2017
BioMed Research International
Volume 2017, Article ID 9393251, 1 page
https://doi.org/10.1155/2017/9393251
Corrigendum to “Functional Virtual Flow Cytometry: A Visual Analytic Approach for Characterizing Single-Cell Gene Expression Patterns”
1College of Software, Nankai University, Tianjin, China
2Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA
3The CCC Biomedical Informatics Shared Resource, The Ohio State University, Columbus, OH, USA
Correspondence should be addressed to Kun Huang; ude.cmuso@gnauh.nuk
Received 18 October 2017; Accepted 26 October 2017; Published 13 November 2017
Copyright © 2017 Zhi Han et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
In the article titled “Functional Virtual Flow Cytometry: A Visual Analytic Approach for Characterizing Single-Cell Gene Expression Patterns” [1], an acknowledgment should be added as follows:
The work was also partially supported by the Shenzhen Peacock Plan (KQTD2016053112051497 to Kun Huang).
References
- Z. Han, T. Johnson, J. Zhang, X. Zhang, and K. Huang, “Functional virtual flow cytometry: a visual analytic approach for characterizing single-cell gene expression patterns,” BioMed Research International, vol. 2017, Article ID 3035481, 9 pages, 2017. View at Publisher · View at Google Scholar