Literature DB >> 24499782

AUTOMATED QUANTIFICATION OF ZEBRAFISH TAIL DEFORMATION FOR HIGH-THROUGHPUT DRUG SCREENING.

Omer Ishaq1, Joseph Negri2, Mark-Anthony Bray2, Alexandra Pacureanu1, Randall T Peterson3, Carolina Wählby4.   

Abstract

Zebrafish (Danio rerio) is an important vertebrate model organism in biomedical research thanks to its ease of handling and translucent body, enabling in vivo imaging. Zebrafish embryos undergo spinal deformation upon exposure to chemical agents that inhibit DNA repair. Automated image-based quantification of spine deformation is therefore attractive for whole-organism based assays for use in early-phase drug discovery. We propose an automated method for accurate high-throughput measurement of tail deformations in multi-fish micro-plate wells. The method generates refined medial representations of partial tail-segments. Subsequently, these disjoint segments are analyzed and fused to generate complete tails. Based on estimated tail curvatures we reach a classification accuracy of 91% on individual animals as compared to known control treatment. This accuracy is increased to 95% when combining scores for fish in the same well.

Entities:  

Keywords:  Curvature extraction; high-throughput screening; quantitative microscopy; zebrafish (Danio rerio)

Year:  2013        PMID: 24499782      PMCID: PMC3909804          DOI: 10.1109/ISBI.2013.6556621

Source DB:  PubMed          Journal:  Proc IEEE Int Symp Biomed Imaging        ISSN: 1945-7928


  10 in total

1.  Fluorescent imaging of cancer in zebrafish.

Authors:  Myron S Ignatius; David M Langenau
Journal:  Methods Cell Biol       Date:  2011       Impact factor: 1.441

2.  Zebrafish as a model organism for the identification and characterization of drugs and genes affecting p53 signaling.

Authors:  Ulrike Langheinrich; Elisabeth Hennen; Gordon Stott; Gabi Vacun
Journal:  Curr Biol       Date:  2002-12-10       Impact factor: 10.834

3.  Research on segmentation of dorsal diencephalon and ventral midbrain of zebrafish embryo based on active contour model.

Authors:  Tao Wu; Jianfeng Lu; Yanting Lu; Jingyu Yang
Journal:  Int J Comput Biol Drug Des       Date:  2012-03-21

Review 4.  Small molecule screening in zebrafish.

Authors:  David S Peal; Randall T Peterson; David Milan
Journal:  J Cardiovasc Transl Res       Date:  2010-08-03       Impact factor: 4.132

Review 5.  Zebrafish: an integrative system for neurogenomics and neurosciences.

Authors:  Silke Rinkwitz; Philippe Mourrain; Thomas S Becker
Journal:  Prog Neurobiol       Date:  2010-12-02       Impact factor: 11.685

6.  Recovering the dynamics of root growth and development using novel image acquisition and analysis methods.

Authors:  Darren M Wells; Andrew P French; Asad Naeem; Omer Ishaq; Richard Traini; Hussein I Hijazi; Hussein Hijazi; Malcolm J Bennett; Tony P Pridmore
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2012-06-05       Impact factor: 6.237

Review 7.  Zebrafish as a cancer model.

Authors:  Harma Feitsma; Edwin Cuppen
Journal:  Mol Cancer Res       Date:  2008-05       Impact factor: 5.852

Review 8.  Animal models of human disease: zebrafish swim into view.

Authors:  Graham J Lieschke; Peter D Currie
Journal:  Nat Rev Genet       Date:  2007-05       Impact factor: 53.242

9.  Modulation of locomotor activity in larval zebrafish during light adaptation.

Authors:  Harold A Burgess; Michael Granato
Journal:  J Exp Biol       Date:  2007-07       Impact factor: 3.312

10.  An image analysis toolbox for high-throughput C. elegans assays.

Authors:  Carolina Wählby; Lee Kamentsky; Zihan H Liu; Tammy Riklin-Raviv; Annie L Conery; Eyleen J O'Rourke; Katherine L Sokolnicki; Orane Visvikis; Vebjorn Ljosa; Javier E Irazoqui; Polina Golland; Gary Ruvkun; Frederick M Ausubel; Anne E Carpenter
Journal:  Nat Methods       Date:  2012-04-22       Impact factor: 28.547

  10 in total
  1 in total

1.  Automated phenotype pattern recognition of zebrafish for high-throughput screening.

Authors:  Mark Schutera; Thomas Dickmeis; Marina Mione; Ravindra Peravali; Daniel Marcato; Markus Reischl; Ralf Mikut; Christian Pylatiuk
Journal:  Bioengineered       Date:  2016-07-03       Impact factor: 3.269

  1 in total

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