Vizardous: interactive analysis of microbial populations with single cell resolution

Helfrich S, Azzouzi CE, Probst C, Seiffarth J, Grünberger A, Wiechert W, Kohlheyer D, Nöh K (2015)
Bioinformatics 31(23): 3875-3877.

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Zeitschriftenaufsatz | Veröffentlicht | Englisch
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Abstract / Bemerkung
Motivation: Single cell time-lapse microscopy is a powerful method for investigating heterogeneous cell behavior. Advances in microfluidic lab-on-a-chip technologies and live-cell imaging render the parallel observation of the development of individual cells in hundreds of populations possible. While image analysis tools are available for cell detection and tracking, biologists are still confronted with the challenge of exploring and evaluating this data. Results: We present the software tool Vizardous that assists scientists with explorative analysis and interpretation tasks of single cell data in an interactive, configurable and visual way. With Vizardous, lineage tree drawings can be augmented with various, time-resolved cellular characteristics. Associated statistical moments bridge the gap between single cell and the population-average level. Availability and implementation: The software, including documentation and examples, is available as executable Java archive as well as in source form at https://github.com/modsim/vizardous. Contact:k.noeh@fz-juelich.de Supplementary information:Supplementary data are available at Bioinformatics online.
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Zeitschriftentitel
Bioinformatics
Band
31
Zeitschriftennummer
23
Seite
3875-3877
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Helfrich S, Azzouzi CE, Probst C, et al. Vizardous: interactive analysis of microbial populations with single cell resolution. Bioinformatics. 2015;31(23):3875-3877.
Helfrich, S., Azzouzi, C. E., Probst, C., Seiffarth, J., Grünberger, A., Wiechert, W., Kohlheyer, D., et al. (2015). Vizardous: interactive analysis of microbial populations with single cell resolution. Bioinformatics, 31(23), 3875-3877. doi:10.1093/bioinformatics/btv468
Helfrich, S., Azzouzi, C. E., Probst, C., Seiffarth, J., Grünberger, A., Wiechert, W., Kohlheyer, D., and Nöh, K. (2015). Vizardous: interactive analysis of microbial populations with single cell resolution. Bioinformatics 31, 3875-3877.
Helfrich, S., et al., 2015. Vizardous: interactive analysis of microbial populations with single cell resolution. Bioinformatics, 31(23), p 3875-3877.
S. Helfrich, et al., “Vizardous: interactive analysis of microbial populations with single cell resolution”, Bioinformatics, vol. 31, 2015, pp. 3875-3877.
Helfrich, S., Azzouzi, C.E., Probst, C., Seiffarth, J., Grünberger, A., Wiechert, W., Kohlheyer, D., Nöh, K.: Vizardous: interactive analysis of microbial populations with single cell resolution. Bioinformatics. 31, 3875-3877 (2015).
Helfrich, Stefan, Azzouzi, Charaf E., Probst, Christopher, Seiffarth, Johannes, Grünberger, Alexander, Wiechert, Wolfgang, Kohlheyer, Dietrich, and Nöh, Katharina. “Vizardous: interactive analysis of microbial populations with single cell resolution”. Bioinformatics 31.23 (2015): 3875-3877.

6 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

Coarse-graining bacteria colonies for modelling critical solute distributions in picolitre bioreactors for bacterial studies on single-cell level.
Westerwalbesloh C, Grünberger A, Wiechert W, Kohlheyer D, von Lieres E., Microb Biotechnol 10(4), 2017
PMID: 28371389
Taking control over microbial populations: Current approaches for exploiting biological noise in bioprocesses.
Delvigne F, Baert J, Sassi H, Fickers P, Grünberger A, Dusny C., Biotechnol J 12(7), 2017
PMID: 28544731
Homogenizing bacterial cell factories: Analysis and engineering of phenotypic heterogeneity.
Binder D, Drepper T, Jaeger KE, Delvigne F, Wiechert W, Kohlheyer D, Grünberger A., Metab Eng 42(), 2017
PMID: 28645641
Image-Based Single Cell Profiling: High-Throughput Processing of Mother Machine Experiments.
Sachs CC, Grünberger A, Helfrich S, Probst C, Wiechert W, Kohlheyer D, Nöh K., PLoS One 11(9), 2016
PMID: 27661996
Modeling and CFD simulation of nutrient distribution in picoliter bioreactors for bacterial growth studies on single-cell level.
Westerwalbesloh C, Grünberger A, Stute B, Weber S, Wiechert W, Kohlheyer D, von Lieres E., Lab Chip 15(21), 2015
PMID: 26345659

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