Yarrow JC, Feng Y, Perlman ZE, Kirchhausen T, Mitchison TJ. Phenotypic screening of small molecule libraries by high throughput cell imaging. Comb Chem High Throughput Screen. 2003;6:279–86. [PubMed]  Boland MV, Murphy RF. A neural network classifier capable of recognizing the patterns of all major subcellular structures in fluorescence microscope images of HeLa cells. Bioinformatics. 2001;17:1213–23. [PubMed]  Perlman ZE, Slack MD, Feng Y, Mitchison TJ, Wu LF, Altschule SJ. Multidimensional drug profiling by automated microscopy. Science. 2004;306:1194–8. [PubMed]  Kiger AA, Baum B, Jones J, Jones MR, Coulson A, Echeverri C, Perrimon N. A functional genomic analysis of cell morphology using rna interference. J Biol. 2:27. [PMC free article] [PubMed]
 Zhou X, Wong STC. Informatics challenges of high-throughput microscopy. IEEE Signal Process Mag. 2006;5:63–72.
 Carpenter A, Jones T, Lamprecht M, Clarke C, Kang I, Friman O, et al. CellProfiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biol. 2006;7(10):R100. [PMC free article] [PubMed]  Wang J, Zhou X, Bradley PL, Chang S-F, Perrimon N, Wong STC. Cellular phenotype recognition for high-content RNAi genome-wide screening. J Biomol Screen. 2008;13(1):29–39. [PubMed]  Settleman J. Rac’n rho: the music that shapes a developing embryo. Dev Cell. 2001;1:321–31. [PubMed]  Yamazaki D, Kurisu S, Takenawa T. Regulation of cancer cell motility through actin reorganization. Cancer Sci. 2005;96:379–86. [PubMed]  Bishop AL, Hall A. Rho gtpases and their effector proteins. Biochem J. 2000;2:241–55. [PubMed]  Burridge K, Wennerberg K. Rho and rac take center stage. Cell. 2004;116:167–79. [PubMed]  Echeverri CJ, Perrimon N. High-throughput rnai screening in cultured cells: a user’s guide. Nat Rev Genet. 2006;7:373–84. [PubMed]  Pham TD, Crane DI, Tran TH, Nguyen TH. Extraction of fluorescent cell puncta by adaptive fuzzy segmentation. Bioinformatics. 2004;20:2189–96. [PubMed]
 Duncan JS, Ayache N. Medical image analysis: progress over two decades and the challenges ahead. IEEE Trans Pattern Anal Mach Intell. 2000;22:85–106.
 Zhou X, Liu KY, Bradley P, Perrimon N, Wong STC. Towards automated cellular image segmentation for rnai genome-wide screening. Lecture Notes in Comp Sci (MICCAI 2005) 2005;3749:885–92. [PubMed]
 Xiong G, Zhou X, Ji L, Bradley P, Perrimon N, Wong STC. Automated segmentation of Drosophila rnai fluorescence cellular images using deformable models. IEEE Trans Circuit Syst. 2006;53:2415–24.
 Li FH, Zhou X, Wong STC. An automated feedback system with the hybrid model of scoring and classification for solving over-segmentation problems in rnai high content screening. J Microsc. 2007;226:121–32. [PubMed]
 Ridler TW, Calvard S. Picture thresholding using an interactive selection method. IEEE Trans Syst, Man, Cybernet. 1978;8:1264–91.
 Manjunath BS, Ma WY. Texture features for browsing and retrieval of image data. IEEE Trans Pattern Anal Mach Intell. 1996;18:837–42.
 Cohen A, Daubechies I, Feauveau JC. Bi-orthogonal bases of compactly supported wavelets. Pure Appl Math. 1992;45:485–560.
 Bovic AC, Clark M, Geisler WS. Multichannel texture analysis using localized spatial filters. IEEE Trans Pattern Anal Mach Intell. 1990;12:55–73.
 Daugman JG. Complete discrete 2-d gabor transforms by neural networks for image analysis and compression. IEEE Trans Acoustics, Speech, Signal Process. 1988;36:1169–79.
 Zernike F. Beugungstheorie des schneidencerfarhens undseiner verbesserten form, der phasenkontrastmethode. Physica. 1934;1:689–704.
 Teague MR. Image analysis via the general theory of moments. Opt Soc Am, J. 1980;70:920–30.
 Haralick RM, Shanmugam K, Dinstein I. Textural features for image classification. IEEE Trans Sys, Man Cybernet. 1973;6:610–20.
 Haralick RM. Statistical and structural approaches to texture. Proc IEEE. 1979;67:786–804.
 Dash M, Liu H. Feature selection for classification. Intell Data Anal. 1997;1(3):131–56.
 Holland JH. Control and artificial intelligence. MIT Press; Cambridge, MA: 1996. Adaptation in natural and artificial systems: an introductory analysis with applications to biology.
 Duda RO, Hart PE, Stork DH. Pattern classification. 2nd ed. Wiley Interscience; New Haven: 2000.
 Burges CJC. A tutorial on support vector machines for pattern recognition. Data Mining Knowledge Discov. 1998;2:121–67.
 Dempster AP, Laird NM, Rubin DB. Maximum-likelihood from incomplete data via the em algorithm. J Royal Statist Soc Ser B. 1977;39:1–38.
 Bilmes JA. Technical Report TR-97-021. International Computer Science Institute; Berkeley, California: 1998. A gentle tutorial of the em algorithm and its applications to parameter estimation for gaussian mixture and hidden markov models.
 Vapnik V. The nature of statistical learning theory. Springer; New York: 1995.
 Kuhn HW, Tucker AW. Nonlinear programming; Proc 2nd Berkeley Symp Math Stat Probabilist; 1951.pp. 481–92.
 Bishop C. Neural networks for pattern recognition. Clarendon Press; Oxford: 1995.