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  Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes.

Neumann, B., Walter, T., Hériché, J.-K., Bulkescher, J., Erfle, H., Conrad, C., et al. (2010). Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes. Nature, 464(7289), 721-727.

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Neumann, Beate, Author
Walter, Thomas1, Author
Hériché, Jean-Karim1, Author
Bulkescher, Jutta, Author
Erfle, Holger, Author
Conrad, Christian, Author
Rogers, Phill, Author
Poser, Ina2, Author           
Held, Michael, Author
Liebel, Urban, Author
Cetin, Cihan, Author
Sieckmann, Frank, Author
Pau, Gregoire, Author
Kabbe, Rolf, Author
Wünsche, Annelie, Author
Satagopam, Venkata, Author
Schmitz, Michael H A, Author
Chapuis, Catherine, Author
Gerlich, Daniel W, Author
Schneider, Reinhard1, Author
Eils, Roland, AuthorHuber, Wolfgang, AuthorPeters, Jan-Michael1, AuthorHyman, Anthony A.2, Author           Durbin, Richard, AuthorPepperkok, Rainer, AuthorEllenberg, Jan, Author more..
Affiliations:
1Max Planck Society, ou_persistent13              
2Max Planck Institute of Molecular Cell Biology and Genetics, Max Planck Society, ou_2340692              

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 Abstract: Despite our rapidly growing knowledge about the human genome, we do not know all of the genes required for some of the most basic functions of life. To start to fill this gap we developed a high-throughput phenotypic screening platform combining potent gene silencing by RNA interference, time-lapse microscopy and computational image processing. We carried out a genome-wide phenotypic profiling of each of the approximately 21,000 human protein-coding genes by two-day live imaging of fluorescently labelled chromosomes. Phenotypes were scored quantitatively by computational image processing, which allowed us to identify hundreds of human genes involved in diverse biological functions including cell division, migration and survival. As part of the Mitocheck consortium, this study provides an in-depth analysis of cell division phenotypes and makes the entire high-content data set available as a resource to the community.

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 Dates: 2010
 Publication Status: Issued
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 Identifiers: eDoc: 546701
Other: 4185
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Title: Nature
Source Genre: Journal
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Pages: - Volume / Issue: 464 (7289) Sequence Number: - Start / End Page: 721 - 727 Identifier: -