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Items: 1 to 20 of 167

1.

A novel phenotypic dissimilarity method for image-based high-throughput screens.

Zhang X, Boutros M.

BMC Bioinformatics. 2013 Nov 21;14:336. doi: 10.1186/1471-2105-14-336.

2.

Using iterative cluster merging with improved gap statistics to perform online phenotype discovery in the context of high-throughput RNAi screens.

Yin Z, Zhou X, Bakal C, Li F, Sun Y, Perrimon N, Wong ST.

BMC Bioinformatics. 2008 Jun 5;9:264. doi: 10.1186/1471-2105-9-264.

3.

Quantitative and automated high-throughput genome-wide RNAi screens in C. elegans.

Squiban B, Belougne J, Ewbank J, Zugasti O.

J Vis Exp. 2012 Feb 27;(60). pii: 3448. doi: 10.3791/3448.

4.

Clustering phenotype populations by genome-wide RNAi and multiparametric imaging.

Fuchs F, Pau G, Kranz D, Sklyar O, Budjan C, Steinbrink S, Horn T, Pedal A, Huber W, Boutros M.

Mol Syst Biol. 2010 Jun 8;6:370. doi: 10.1038/msb.2010.25.

5.

Simultaneous analysis of large-scale RNAi screens for pathogen entry.

Rämö P, Drewek A, Arrieumerlou C, Beerenwinkel N, Ben-Tekaya H, Cardel B, Casanova A, Conde-Alvarez R, Cossart P, Csúcs G, Eicher S, Emmenlauer M, Greber U, Hardt WD, Helenius A, Kasper C, Kaufmann A, Kreibich S, Kühbacher A, Kunszt P, Low SH, Mercer J, Mudrak D, Muntwiler S, Pelkmans L, Pizarro-Cerdá J, Podvinec M, Pujadas E, Rinn B, Rouilly V, Schmich F, Siebourg-Polster J, Snijder B, Stebler M, Studer G, Szczurek E, Truttmann M, von Mering C, Vonderheit A, Yakimovich A, Bühlmann P, Dehio C.

BMC Genomics. 2014 Dec 22;15:1162. doi: 10.1186/1471-2164-15-1162.

6.

High-throughput RNAi screening for the identification of novel targets.

Henderson MC, Azorsa DO.

Methods Mol Biol. 2013;986:89-95. doi: 10.1007/978-1-62703-311-4_6.

PMID:
23436407
7.

HCS-Neurons: identifying phenotypic changes in multi-neuron images upon drug treatments of high-content screening.

Charoenkwan P, Hwang E, Cutler RW, Lee HC, Ko LW, Huang HL, Ho SY.

BMC Bioinformatics. 2013;14 Suppl 16:S12. doi: 10.1186/1471-2105-14-S16-S12.

8.

Unsupervised automated high throughput phenotyping of RNAi time-lapse movies.

Failmezger H, Fröhlich H, Tresch A.

BMC Bioinformatics. 2013 Oct 4;14:292. doi: 10.1186/1471-2105-14-292.

9.

High-throughput RNAi screening by time-lapse imaging of live human cells.

Neumann B, Held M, Liebel U, Erfle H, Rogers P, Pepperkok R, Ellenberg J.

Nat Methods. 2006 May;3(5):385-90.

PMID:
16628209
10.

Large-scale tracking and classification for automatic analysis of cell migration and proliferation, and experimental optimization of high-throughput screens of neuroblastoma cells.

Harder N, Batra R, Diessl N, Gogolin S, Eils R, Westermann F, König R, Rohr K.

Cytometry A. 2015 Jun;87(6):524-40. doi: 10.1002/cyto.a.22632.

11.

A Multivariate Computational Method to Analyze High-Content RNAi Screening Data.

Rameseder J, Krismer K, Dayma Y, Ehrenberger T, Hwang MK, Airoldi EM, Floyd SR, Yaffe MB.

J Biomol Screen. 2015 Sep;20(8):985-97. doi: 10.1177/1087057115583037.

PMID:
25918037
12.

GUItars: a GUI tool for analysis of high-throughput RNA interference screening data.

Goktug AN, Ong SS, Chen T.

PLoS One. 2012;7(11):e49386. doi: 10.1371/journal.pone.0049386.

13.

Towards automated cellular image segmentation for RNAi genome-wide screening.

Zhou X, Liu KY, Bradley P, Perrimon N, Wong ST.

Med Image Comput Comput Assist Interv. 2005;8(Pt 1):885-92.

PMID:
16685930
14.

An image score inference system for RNAi genome-wide screening based on fuzzy mixture regression modeling.

Wang J, Zhou X, Li F, Bradley PL, Chang SF, Perrimon N, Wong ST.

J Biomed Inform. 2009 Feb;42(1):32-40. doi: 10.1016/j.jbi.2008.04.007.

15.

High-throughput RNAi in Caenorhabditis elegans: genome-wide screens and functional genomics.

Sugimoto A.

Differentiation. 2004 Mar;72(2-3):81-91. Review.

PMID:
15066188
16.

Genome-wide screening for gene function using RNAi in mammalian cells.

Cullen LM, Arndt GM.

Immunol Cell Biol. 2005 Jun;83(3):217-23. Review.

PMID:
15877598
17.

From sequence to function: using RNAi to elucidate mechanisms of human disease.

Wolters NM, MacKeigan JP.

Cell Death Differ. 2008 May;15(5):809-19. doi: 10.1038/sj.cdd.4402311. Review.

18.

High-throughput RNA interference strategies for target discovery and validation by using synthetic short interfering RNAs: functional genomics investigations of biological pathways.

Sachse C, Krausz E, Krönke A, Hannus M, Walsh A, Grabner A, Ovcharenko D, Dorris D, Trudel C, Sönnichsen B, Echeverri CJ.

Methods Enzymol. 2005;392:242-77.

PMID:
15644186
19.

iScreen: Image-Based High-Content RNAi Screening Analysis Tools.

Zhong R, Dong X, Levine B, Xie Y, Xiao G.

J Biomol Screen. 2015 Sep;20(8):998-1002. doi: 10.1177/1087057114564348.

PMID:
25548139
20.

Automatic identification and clustering of chromosome phenotypes in a genome wide RNAi screen by time-lapse imaging.

Walter T, Held M, Neumann B, Hériché JK, Conrad C, Pepperkok R, Ellenberg J.

J Struct Biol. 2010 Apr;170(1):1-9. doi: 10.1016/j.jsb.2009.10.004.

PMID:
19854275
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