Format
Sort by
Items per page

Send to

Choose Destination

Links from PubMed

Items: 1 to 20 of 118

1.

Algorithmic Tools for Mining High-Dimensional Cytometry Data.

Chester C, Maecker HT.

J Immunol. 2015 Aug 1;195(3):773-9. doi: 10.4049/jimmunol.1500633. Review.

2.

The end of gating? An introduction to automated analysis of high dimensional cytometry data.

Mair F, Hartmann FJ, Mrdjen D, Tosevski V, Krieg C, Becher B.

Eur J Immunol. 2016 Jan;46(1):34-43. doi: 10.1002/eji.201545774. Epub 2015 Nov 30. Review.

3.

Unfold High-Dimensional Clouds for Exhaustive Gating of Flow Cytometry Data.

Qiu P.

IEEE/ACM Trans Comput Biol Bioinform. 2014 Nov-Dec;11(6):1045-51. doi: 10.1109/TCBB.2014.2321403.

4.

immunoClust--An automated analysis pipeline for the identification of immunophenotypic signatures in high-dimensional cytometric datasets.

Sörensen T, Baumgart S, Durek P, Grützkau A, Häupl T.

Cytometry A. 2015 Jul;87(7):603-15. doi: 10.1002/cyto.a.22626. Epub 2015 Apr 7.

5.

Deep Profiling Human T Cell Heterogeneity by Mass Cytometry.

Cheng Y, Newell EW.

Adv Immunol. 2016;131:101-34. doi: 10.1016/bs.ai.2016.02.002. Epub 2016 Apr 8. Review.

PMID:
27235682
6.

Antigen-specific cytometry--new tools arrived!

Thiel A, Scheffold A, Radbruch A.

Clin Immunol. 2004 May;111(2):155-61. Review.

PMID:
15137948
7.

Comparison of clustering methods for high-dimensional single-cell flow and mass cytometry data.

Weber LM, Robinson MD.

Cytometry A. 2016 Dec;89(12):1084-1096. doi: 10.1002/cyto.a.23030. Epub 2016 Dec 19.

8.

AutoGate: automating analysis of flow cytometry data.

Meehan S, Walther G, Moore W, Orlova D, Meehan C, Parks D, Ghosn E, Philips M, Mitsunaga E, Waters J, Kantor A, Okamura R, Owumi S, Yang Y, Herzenberg LA, Herzenberg LA.

Immunol Res. 2014 May;58(2-3):218-23. doi: 10.1007/s12026-014-8519-y.

9.

Identifying Cell Populations in Flow Cytometry Data Using Phenotypic Signatures.

Pouyan MB, Nourani M.

IEEE/ACM Trans Comput Biol Bioinform. 2017 Jul-Aug;14(4):880-891. doi: 10.1109/TCBB.2016.2550428. Epub 2016 Apr 5.

PMID:
27076456
10.

Probability state modeling theory.

Bagwell CB, Hunsberger BC, Herbert DJ, Munson ME, Hill BL, Bray CM, Preffer FI.

Cytometry A. 2015 Jul;87(7):646-60. doi: 10.1002/cyto.a.22687. Epub 2015 May 25.

11.

Automated identification of stratifying signatures in cellular subpopulations.

Bruggner RV, Bodenmiller B, Dill DL, Tibshirani RJ, Nolan GP.

Proc Natl Acad Sci U S A. 2014 Jul 1;111(26):E2770-7. doi: 10.1073/pnas.1408792111. Epub 2014 Jun 16.

12.

FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data.

Van Gassen S, Callebaut B, Van Helden MJ, Lambrecht BN, Demeester P, Dhaene T, Saeys Y.

Cytometry A. 2015 Jul;87(7):636-45. doi: 10.1002/cyto.a.22625. Epub 2015 Jan 8.

14.

Flow cytometry data analysis: Recent tools and algorithms.

Montante S, Brinkman RR.

Int J Lab Hematol. 2019 May;41 Suppl 1:56-62. doi: 10.1111/ijlh.13016. Review.

PMID:
31069980
15.

Multi-parametric cytometry from a complex cellular sample: Improvements and limits of manual versus computational-based interactive analyses.

Gondois-Rey F, Granjeaud S, Rouillier P, Rioualen C, Bidaut G, Olive D.

Cytometry A. 2016 May;89(5):480-90. doi: 10.1002/cyto.a.22850. Epub 2016 Apr 5.

16.

Identification and visualization of multidimensional antigen-specific T-cell populations in polychromatic cytometry data.

Lin L, Frelinger J, Jiang W, Finak G, Seshadri C, Bart PA, Pantaleo G, McElrath J, DeRosa S, Gottardo R.

Cytometry A. 2015 Jul;87(7):675-82. doi: 10.1002/cyto.a.22623. Epub 2015 Apr 23.

17.

SWIFT-scalable clustering for automated identification of rare cell populations in large, high-dimensional flow cytometry datasets, part 2: biological evaluation.

Mosmann TR, Naim I, Rebhahn J, Datta S, Cavenaugh JS, Weaver JM, Sharma G.

Cytometry A. 2014 May;85(5):422-33. doi: 10.1002/cyto.a.22445. Epub 2014 Feb 14.

18.

Comparative exploration of multidimensional flow cytometry software: a model approach evaluating T cell polyfunctional behavior.

Spear TT, Nishimura MI, Simms PE.

J Leukoc Biol. 2017 Aug;102(2):551-561. doi: 10.1189/jlb.6A0417-140R. Epub 2017 May 26.

PMID:
28550117
19.

Computational prediction of manually gated rare cells in flow cytometry data.

Qiu P.

Cytometry A. 2015 Jul;87(7):594-602. doi: 10.1002/cyto.a.22654. Epub 2015 Mar 9.

20.

A theorem proving approach for automatically synthesizing visualizations of flow cytometry data.

Raj S, Hussain F, Husein Z, Torosdagli N, Turgut D, Deo N, Pattanaik S, Chang CJ, Jha SK.

BMC Bioinformatics. 2017 Jun 7;18(Suppl 8):245. doi: 10.1186/s12859-017-1662-4.

Supplemental Content

Support Center