Proc Natl Inst Sci India 2:49–55Ĭonrad C, Gerlich DW (2010) Automated microscopy for high-content RNAi screening.
Cellprofiler custom script Pc#
Mahalanobis PC (1936) On the generalised distance in statistics. Shun TY, Lazo JS, Sharlow ER et al (2011) Identifying actives from HTS data sets. J Biomol Screen 8:634–647īirmingham A, Selfors LM, Forster T et al (2009) Statistical methods for analysis of high-throughput RNA interference screens. Phil Trans Roy Soc London Ser A 187:253–318īrideau C, Gunter B, Pikounis B et al (2003) Improved statistical methods for hit selection in high-throughput screening. Pearson K (1896) Mathematical contributions to the theory of evolution. Moddemeijer R (1999) A statistic to estimate the variance of the histogram based mutual information estimator based on dependent pairs of observations. D, (2007) A pair of new statistical parameters for quality control in RNA interference high-throughput screening assays, Genomics 89:552–561 Zhang J-H, Chung TDY, Oldenburg KR (1999) A simple statistical parameter for use in evaluation and validation of high throughput screening assays.
Cellprofiler custom script software#
Jones T, Kang I, Wheeler D et al (2008) CellProfiler analyst: data exploration and analysis software for complex image-based screens. Jones R, Carpenter E, Lamprecht R et al (2009) Scoring diverse cellular morphologies in image-based screens with iterative feedback and machine learning. Bioinformatics 27:1179–1180īray M-A, Fraser AN, Hasaka TP et al (2011) Workflow and metrics for image quality control in large-scale high-content screens. Kamentsky L, Jones TR, Fraser A et al (2011) Improved structure, function and compatibility for CellProfiler: modular high-throughput image analysis software. ASSAY Drug Devel Technol 6:693–710Ĭarpenter A, Jones T, Lamprecht M et al (2006) Cell Profiler: image analysis software for identifying and quantifying cell phenotypes. Santos AF, Zaltsman AB, Martin RC et al (2008) Angiogenesis: an improved in vitro biological system and automated image-based workflow to aid identification and characterization of angiogenesis and angiogenic modulators. Curr Pharmaceut Biotechnol 11:764–778ĭ’Ausilio A (2012) Arduino: a low-cost multi purpose lab equipment. Roy A, McDonald PR, Sittampalam S, Chaguturu R (2010) Open access high throughput drug discovery in the public domain: a mount everest in the making. Hunter P (2010) Facing the credit crunch.
Gulledge J (2011) Debt crisis: crunch time for US science. Holt R (2011) Dueling visions for science. Am J Physiol: Cell Physiol 286:C465–C474Ĭressey D (2011) Drug-maker plans to cut jobs and spending as industry shies away from drug discovery. Verkman AS (2004) Drug discovery in academia. Giuliano KA, DeBiasio RL, Dunlay RT et al (1997) High-content screening: a new approach to easing key bottlenecks in the drug discovery process. Ortholand J-Y, Ganesan A (2004) Natural products and combinatorial chemistry: back to the future. Newman DJ, Cragg GM, Snader KM (2003) Natural products as sources of new drugs over the period 1981–2002. J Forensic Sci 20:17Īrcher JR (2004) History evolution, and trends in compound management for high throughput screening. Annu Rev Biophys Bioeng 4:529–577īlackwell RJ, Crisci WA (1975) Digital image processing technology and its application in forensic sciences. Lipkin LE, Lipkin BS (1975) Computers in the clinical pathologic laboratory: chemistry and image processing. Harmon LD, Knowlton KC (1969) Picture processing by computer. Johnston AR, Powell RV (1970) Optics at the Jet Propulsion Laboratory. We present and discuss the Open Source software CellProfiler for image analysis and KNIME for data analysis and data mining that provide software solutions which increase flexibility and keep costs low. Many cost factors cannot be avoided, but the costs of the software packages necessary to analyze large datasets can be reduced by using Open Source software. Flexibility is important to be able to adapt the HCS setup to accommodate the multiple different assays typical of academia. One of the limitations in the establishment of HCS in academia is flexibility and cost.
Given the diversity of problems tackled in academic research, HCS could experience some profound changes in the future, mainly with more imaging modalities and smart microscopes being developed. HCS is currently starting to enter the academic world and might become a widely used technology.
High content screening (HCS) has established itself in the world of the pharmaceutical industry as an essential tool for drug discovery and drug development.
0 kommentar(er)
