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This version of GCellIQ (Version 1.0) can only run on a machine with Matlab installed. No other installation is required for this software. Just copy the source code into local disk and run the program under Matlab environment. Please read and agree the license before running the program.

Project Manager: Zheng Yin, Ph.D.
Documentation: Zhuhong You, Xiaobo Zhou, Zheng Yin
Funding Support: NIH NCI R01CA121225
Bioinformatics Program, The Methodist Hospital Research Institute, Houston, Texas
PI: Professor Stephen Wong

Key Collaborators:
Professor Norbert Perrimon, Ph.D. and Dr. Chris Bakal, Department of Genetics, Harvard Medical School. http://genepath.med.harvard.edu/

We acknowledge the productive collaboration with Professor Norbert Perrimon and Dr. Chris Bakal in the development of GCellIQ and appreciate the valuable feedbacks on the earlier GCellIQ prototype from his lab.


References:

1. Li F, Zhou X, Zhu J, Ma J, Huang X, et al. (2007) High content image analysis for human H4 neuroglioma cells exposed to CuO nanoparticles. Bmc Biotechnology 7: p. 66.

2. Wang J, Zhou X, Bradley PL, Chang SF, Perrimon N, et al. (2008) Cellular phenotype recognition for high-content RNA interference genome-wide screening. Journal of Biomolecular Screening 13: 29-39.

3. Manjunath BS, Ma WY (1996) Texture features for browsing and retrieval of image data. Ieee Transactions on Pattern Analysis and Machine Intelligence 18: 837-842.

4. Cohen A, Daubechies I, Feauveau JC (1992) Biorthogonal Bases of Compactly Supported Wavelets. Communications on Pure and Applied Mathematics 45: 485-560.

5. F Z (1934) Beugungstheorie des schneidencerfarhens undseiner verbesserten form, der phasenkontrastmethode. Physica 1: 689-704.

6. M HR, K S, I D (1973) Textural features for image classification. Transactions on Systems, Man and Cybernetics 6: 610-620.