TY - JOUR
T1 - Informatics challenges of high-throughput microscopy
AU - Zhou, Xiaobo
AU - Wong, Stephen T.C.
N1 - Funding Information:
Tim Mitchison, Department of Systems Biology, Harvard Medical School; Prof. Tom Kirchhausen, CBR Center for Biomedical Research, Harvard Medical School; Prof. Randy King, Department of Cell Biology, Harvard Medical School; and Prof. Norbert Perrimon, Department of Genetics, Harvard Medical School. The raw image data described in this article were obtained from our biological collaborators’ laboratories. The image processing and computational modeling work are the contribution of the authors with the input of other members of the life science imaging group of HCNR-Center for Bioinformatics, notably Mr. Xiaowei Chen, Dr. Xiaoyin Xu, Dr. Jinmin Zhu, Dr. Kuang-Yu Liu, and Dr. Xinhua Cao. This research is funded by the HCNR Center for Bioinformatics Research Grant, Harvard Medical School, and a NIH R01 LM008696 Grant to STCW.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2006/5
Y1 - 2006/5
N2 - High-throughput screening (HTS) using automated fluorescence microscopy technology, also known as high-content screening (HCS) is becoming an important tool to assist scientists in understanding the complex processes of cell division or mitosis, disease diagnosis and prognosis, drug target validation, and compound lead selection. Automated, high-throughput microscopy can be considered as consisting of six modules: biological experiments and image acquisition; image processing and analysis; quantitative feature extraction and database storage; validation; data modeling and statistical analysis; and visualization. For demonstration purposes, four examples of biological experiments of HTS are presented: cell cycle analysis for time-lapse microscopy screens; genome-wide RNAi screening in drosophila cells; monastrol suppressor drugs; and dynamic subcellular particle detection and tracking.
AB - High-throughput screening (HTS) using automated fluorescence microscopy technology, also known as high-content screening (HCS) is becoming an important tool to assist scientists in understanding the complex processes of cell division or mitosis, disease diagnosis and prognosis, drug target validation, and compound lead selection. Automated, high-throughput microscopy can be considered as consisting of six modules: biological experiments and image acquisition; image processing and analysis; quantitative feature extraction and database storage; validation; data modeling and statistical analysis; and visualization. For demonstration purposes, four examples of biological experiments of HTS are presented: cell cycle analysis for time-lapse microscopy screens; genome-wide RNAi screening in drosophila cells; monastrol suppressor drugs; and dynamic subcellular particle detection and tracking.
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U2 - 10.1109/MSP.2006.1628879
DO - 10.1109/MSP.2006.1628879
M3 - Article
AN - SCOPUS:85032752151
SN - 1053-5888
VL - 23
SP - 63
EP - 72
JO - IEEE Signal Processing Magazine
JF - IEEE Signal Processing Magazine
IS - 3
ER -