ArticleBioinformatics (Oxford, England)2012
CellAnimation: an open source MATLAB framework for microscopy assays.
Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed.
- ACDC: Automated Cell Detection and Counting for Time-Lapse Fluorescence Microscopy.Applied sciences (Basel, Switzerland) · 2020Article
- Article
- Article
- Image-Based Tracking of Heterogeneous Single-Cell Phenotypes.Methods in molecular biology (Clifton, N.J.) · 2018Article
- A Predictive Mathematical Modeling Approach for the Study of Doxorubicin Treatment in Triple Negative Breast Cancer.Scientific reports · 2017Article
- Cell and small animal models for phenotypic drug discovery.Drug design, development and therapy · 2017Review
- Influence of Stress and Antibiotic Resistance on Cell-Length Distribution inFrontiers in microbiology · 2017Article
- Single cell dynamic phenotyping.Scientific reports · 2016Article
- Quantifying heterogeneity and dynamics of clonal fitness in response to perturbation.Journal of cellular physiology · 2015Article
- Automated analysis of cell-matrix adhesions in 2D and 3D environments.Scientific reports · 2015Article
- Article
- The formation of tight tumor clusters affects the efficacy of cell cycle inhibitors: a hybrid model study.Journal of theoretical biology · 2014Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
motivationAdvances in microscopy technology have led to the creation of high-throughput microscopes that are capable of generating several hundred gigabytes of images in a few days. Analyzing such wealth of data manually is nearly impossible and requires an automated approach. There are at present a number of open-source and commercial software packages that allow the user to apply algorithms of different degrees of sophistication to the images and extract desired metrics. However, the types of metrics that can be extracted are severely limited by the specific image processing algorithms that the application implements, and by the expertise of the user. In most commercial software, code unavailability prevents implementation by the end user of newly developed algorithms better suited for a particular type of imaging assay. While it is possible to implement new algorithms in open-source software, rewiring an image processing application requires a high degree of expertise. To obviate these limitations, we have developed an open-source high-throughput application that allows implementation of different biological assays such as cell tracking or ancestry recording, through the use of small, relatively simple image processing modules connected into sophisticated imaging pipelines. By connecting modules, non-expert users can apply the particular combination of well-established and novel algorithms developed by us and others that are best suited for each individual assay type. In addition, our data exploration and visualization modules make it easy to discover or select specific cell phenotypes from a heterogeneous population. AVAILABILITY: CellAnimation is distributed under the Creative Commons Attribution-NonCommercial 3.0 Unported license (http://creativecommons.org/licenses/by-nc/3.0/). CellAnimationsource code and documentation may be downloaded from www.vanderbilt.edu/viibre/software/documents/CellAnimation.zip. Sample data are available at www.vanderbilt.edu/viibre/software/documents/movies.zip. CONTACT: walter.georgescu@vanderbilt.edu SUPPLEMENTARY INFORMATION: Supplementary data available at Bioinformatics online.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.