181738760X     

Normalizing for individual cell population context in the analysis of high-content cellular screens / Bettina Knapp, Ilka Rebhan, Anil Kumar, Petr Matula, Narsis A. Kiani, Marco Binder, Holger Erfle, Karl Rohr, Roland Eils, Ralf Bartenschlager and Lars Kaderali

Knapp, Bettina [Verfasserin/Verfasser]

Rebhan, Ilka [Verfasserin/Verfasser] ; Kumar, Anil [Verfasserin/Verfasser] ; Matula, Petr [Verfasserin/Verfasser] ; Kiani, Narsis, 1978- [Verfasserin/Verfasser] ; Binder, Marco [Verfasserin/Verfasser] ; Erfle, Holger [Verfasserin/Verfasser] ; Rohr, Karl [Verfasserin/Verfasser] ; Eils, Roland, 1965- [Verfasserin/Verfasser] ; Bartenschlager, Ralf, 1958- [Verfasserin/Verfasser] ; Kaderali, Lars, 1974- [Verfasserin/Verfasser]

BMC bioinformatics. - London : BioMed Central ; Berlin, Heidelberg : Springer, 2000-. - Bd. 12 (2011), S. 1-14 = 14 S.

Englisch

Gesehen am 26.09.2022

Elektronische Ressource: Zugang beim Produzenten (Lizenzangabe: Lizenzpflichtig)

Digital Object Identifier (DOI): 10.1186/1471-2105-12-485

Dengue Virus Infection ; DENV Infection ; Multivariate Adaptive Regression Spline ; Population Context ; RNAi Screen

High-content, high-throughput RNA interference (RNAi) offers unprecedented possibilities to elucidate gene function and involvement in biological processes. Microscopy based screening allows phenotypic observations at the level of individual cells. It was recently shown that a cell's population context significantly influences results. However, standard analysis methods for cellular screens do not currently take individual cell data into account unless this is important for the phenotype of interest, i.e. when studying cell morphology.