Computational systems bioinformatics and bioimaging for pathway analysis and drug screening

Proceedings of the IEEE

Volumn 96, Issue 8, 2008, Pages 1310-1331

  Zhou, Xiaobo ^a   Wong, Stephen T C ^a  

^a WEILL CORNELL MEDICAL COLLEGE   (United States)

Author keywords

Biomarker discovery; Drug discovery; High content screen; High throughput screen; RNAi; System bioinformatics and bioimaging; Target validation

Indexed keywords

BIOINFORMATICS; COORDINATION REACTIONS; DIAGNOSIS; DRUG PRODUCTS; GENES; METABOLITES; MOLECULAR BIOLOGY;

BIO-IMAGING; BIO-MARKER DISCOVERY; DRUG DISCOVERY; HIGH CONTENT SCREEN; HIGH-THROUGHPUT SCREENS; RNAI; TARGET VALIDATIONS;

PROTEINS;

EID: 47949110106     PISSN: 00189219     EISSN: None     Source Type: Journal    
DOI: 10.1109/JPROC.2008.925440     Document Type: Article

References (90)

1. H. Kitano, "Systems biology: A brief overview," Science, vol. 295, no. 5560, pp. 1662-1664.
2. R. W. Carthew, "Gene silencing by double-stranded RNA," Curr. Opin. Cell Biol., vol. 13, no. 2, pp. 244-248, 2001.
3. E. J. Roques and R. F. Murphy, "Objective evaluation of differences in protein subcellular distribution," Traffic, vol. 3, no. 1, pp. 61-65, 2002.
4. T. R. Jones, A. E. Carpenter, and P. Golland, "Voronoi-based segmentation of cells on image manifolds," in Proc. ICCV Worfeshop Comput. Vision Biomed. Image Applicat., 2005, pp. 535-543.
5. R. Kapur, "High content screening and the CellChip-TM system: Living cells as beacons for drugs and toxins," Eur. Cells Mater., vol. 2, no. Suppl. 1, p. 7, 2001.
6. M. Morelock, E. Hunter, T. Moran, S. Heynen, C. Laris, M. Thieleking, M. Akong, I. Mike, S. Callaway, R. DeLeon, A. Goodacre, D. Zacharias, and J. Price, "Statistics of assay validation in high throughput cell imaging of nuclear facter kB nuclear translocation," ASSAY Drug Develop. Technol., vol. 3, no. 5, pp. 483-499, 2005.
7. N. Ray, S. T. Acton, and K. Ley, "Tracking leukocytes in vivo with shape and size constrained active contours," IEEE Trans. Med. Imag., vol. 21, no. 10, pp. 1222-1235, 2002.
8. C. Zimmer and J.-C. Olivo-Marin, "Coupled parametric active contours," IEEE Trans. Pattern Anal Mach. Intell., vol. 27, no. 11, pp. 1838-1842, 2005.
9. C. Zimmer et al., "Segmentation and tracking of migrating cells in videomicroscopy with parametric active contours: A tool for cell-based drug testing," IEEE Trans. Med. Imag., vol. 21, no. 10, pp. 1212-1221, 2002.
10. A. Ben-Hur, A. Elisseeff, and I. Guyon, "A stability based method for discovering structure in clustered data," in Proc. Pac. Symp. Biocomput., 2002, pp. 6-17.
11. L. Li et al., "Gene selection for sample classification based on gene expression data: Study of sensitivity to choice of parameters of the GA/KNN method," Bioinformatics, vol. 17, no. 12, pp. 1131-1142, 2001.
12. S. Kim et al., "Strong feature sets from small samples," J. Comput. Biol., vol. 9, no. 1, pp. 127-146, 2002.
13. K. E. Lee et al., "Gene selection: A Bayesian variable selection approach," Bioinformatics, vol. 19, no. 1, pp. 90-97, 2003.
14. X. Zhou, X. Wang, and E. R. Dougherty, "Multi-class cancer classification using multinomial probit regression with Bayesian gene selection," Inst. Elect. Eng. Syst. Biol., vol. 153, no. 2, pp. 70-78, 2006.
15. T. R. Golub et al., "Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring," Science, vol. 286, no. 5439, pp. 531-537, 1999.
16. X. Zhou, X. Wang, and E. R. Dougherty, "Nonlinear probit gene classification using mutual-information and wavelet," J. Biol. Syst., vol. 12, no. 3, pp. 371-386, 2004.
17. X. Zhou, K. Y. Liu, and S. T. Wong, "Cancer classification and prediction using logistic regression with Bayesian gene selection," J Biomed. Inf., vol. 37, no. 4, pp. 249-259, 2004.
18. A. M. Zoubir and B. Boashash, "The bootstrap and its application in signal processing," IEEE Signal Process. Mag., vol. 15, no. 1, pp. 56-76, 1998.
19. E. Xing, M. Jordan, and R. Karp, "Feature selection for high dimensional genomic microarray data," in Proc. 8th Int. Conf. Mach. Learn., Williamstown, MA, 2001.
20. J. Albert and S. Chib, "Bayesian analysis of binary and polychotomous response data," J. Amer. Stat. Assoc., vol. 88, pp. 669-679, 1993.
21. E. Petricoin, "Use of proteomic patterns in serum to identify ovarian cancer," Lancet, vol. 359, no. 9306, pp. 572-577, 2002.
22. P. Berndt, U. Hobohm, and H. Langen, "Reliable automatic protein identification from matrix-assistant laser desorption/ionization mass spectrometric peptide fingerprints," Electrophoresis, vol. 20, pp. 3521-3526, 1999.
23. Y. Yasui et al., "An automated peak identification/ calibration procedure for high-dimensional protein measures from mass spectrometers," J. Biomed. Biotechnol., vol. 2003, no. 4, pp. 242-248, 2003.
24. J. S. Morris et al., "Feature extraction and quantification for mass spectrometry in biomedical applications using the mean spectrum," Bioinformatics, vol. 21, no. 9, pp. 1764-1775, 2005.
25. P. Du, W. A. Kibbe, and S. M. Lin, "Improved peak detection in mass spectrum by incorporating continuous wavelet transform-based pattern matching," Bioinformatics, vol. 22, no. 17, pp. 2059-2065, 2006.
26. W. Yu, B. Wu, N. Lin, K. Stone, K. Williams, and H. Zhao, "Detecting and aligning peaks in mass spectrometry data with applications to MALDI," Comput. Biol. Chem., vol. 30, pp. 27-38, 2006.
27. R. Kohavi and G. H. John, "Wrappers for feature subset selection," Artif. Intell., vol. 97, no. 1-2, pp. 273-324, 1997.
28. X. Zhou, H. Wang, J. Wang, G. Hoehn, J. Azok, M. L. Brennan, S. L. Hazen, K. Li, and S. T. C. Wong, "Biomarker discovery for risk stratification of cardiovascular events using an improved genetic algorithm," in Proc. IEEE/NIM International Workshop on Life Science Systems and Applications, pp. 42-44, July 13-14, 2006.
29. X. Zhou et al., "A Bayesian connectivity-based approach to constructing probabilistic gene regulatory networks," Bioinformatics, vol. 20, no. 17, pp. 2918-2927, 2004.
30. U. Sauer, M. Heinemann, and N. Zamboni, "Genetics. Getting closer to the whole picture," Science, vol. 316, no. 5824, pp. 550-551, 2007.
31. R. S. Wang et al., "Inferring transcriptional regulatory networks from high-throughput data," Bioinformatics, vol. 23, no. 22, pp. 3056-3064, 2007.
32. Y. Wang et al., "Inferring gene regulatory networks from multiple microarray datasets," Bioinformatics, vol. 22, no. 19, pp. 2413-2420, 2006.
33. M. K. Yeung, J. Tegner, and J. J. Collins, "Reverse engineering gene networks using singular value decomposition and robust regression," Proc. Nat. Acad. Sci. USA, vol. 99, no. 9, pp. 6163-6168, 2002.
34. C. H. Yeang and M. Vingron, "A joint model of regulatory and metabolic networks," Bioinformatics, vol. 7, p. 332, 2006.
35. E. Segal, H. Wang, and D. Koller, "Discovering molecular pathways from protein interaction and gene expression data," Bioinformatics, vol. 19, pp. i264-i271, 2003. suppl. 1.
36. Y. Yamanishi, J. P. Vert, and M. Kanehisa, "Supervised enzyme network inference from the integration of genomic data and chemical information," Bioinformatics, vol. 2, pp. i468-i477, 2005. suppl. 1.
37. X. Zhou and S. T. C. Wong, "Informatics challenges of high-throughput cellular and molecular microscopy," IEEE Signal Process. Mag., vol. 23, no. 3, pp. 63-72, 2006.
38. A. A. Kiger et al., "A functional genomic analysis of cell morphology using RNA interference," J. Biol., vol. 2, no. 4, p. 27, 2003.
39. J. Lindblad et al., "Image analysis for automatic segmentation of cytoplasms and classification of Racl activation," Cytometry A, vol. 57, no. 1, pp. 22-33, 2004.
40. V. Caselles, R. Kimmel, and G. Sapiro, "Geodesic active contours," Int. J. Comput. Vision, vol. 22, no. 1, pp. 61-79, 1997.
41. G. Xiong, X. Zhou, and L. Ji, "Automated segmentation of Drosophila RNAi fluorescence cellular images using deformable models," IEEE Trans. Circuits Syst. I, Reg. papers, vol. 53, no. 11, pp. 2415-2424, 2006.
42. R. Deriche, "Fast algorithms for low-level vision," IEEE Trans. Pattern Anal. Mach. Intell., vol. 12, no. 1, pp. 78-87, 1990.
43. J. A. Sethian, "Level set methods: evolving interfaces in geometry, fluid mechanics, computer vision, and materials science," in Cambridge Monographs on Applied and Computational Mathematics, vol. 3. Cambridge, U.K.: Cambridge Univ. Press, 1996, p. xviii.
44. P. Yan, X. Zhou, M. Shah, and S. T. C. Wong, "Automatic segmentation of RNAi fluorescent cellular images with interaction model," IEEE Trans. Inf. Technol. Biomed., to be published.
45. F. Li et al., "An automated feedback system with the hybrid model of scoring and classification for solving over-segmentation problems in RNAi high content screening," J. Microsc., vol. 226, pt. 2, pp. 121-132, 2007.
46. J. Wang, X. Zhou, P. L. Bradley, N. Perrimon, and S. T. C. Wong, "Henotype recognition for high-content RNAi genome-wide screening," I. Mol. Screening, 2007, to be published.
47. B. Efron et al., "Empirical Bayes analysis of a microarray experiment," J. Amer. Statist. Assoc., vol. 96, no. 456, pp. 1151-1160, 2001.
48. B. Sonnichsen et al., "Full-genome RNAi profiling of early embryogenesis in Caenorhabditis elegans," Nature, vol. 434, no. 7032, pp. 462-469, 2005.
49. C. Sachse et al., "High-throughput RNA interference strategies for target discovery and validation by using synthetic short interfering RNAs: Functional genomics investigations of biological pathways," Meth. Enzymol., vol. 392, pp. 242-277, 2005.
50. K. C. Gunsalus et al., "Predictive models of molecular machines involved in Caenorhabditis elegans early embryogenesis," Nature, vol. 436, no. 7052, pp. 861-865, 2005.
51. T. J. Shors, C. Chua, and J. Falduto, "Sex differences and opposite effects of stress on dendritic spine density in the male versus female hippocampus," J. Neurosci., vol. 21, no. 16, pp. 6292-6297, 2001.
52. I. Lolova, "Dendritic changes in the hippocampus of aged rats," Acta Morphol. Hung., vol. 37, no. 1-2, pp. 3-10, 1989.
53. B. D. Philpot et al., "Visual experience and deprivation bidirectionally modify the composition and function of NMDA receptors in visual cortex," Neuron, vol. 29, no. 1, pp. 157-169, 2001.
54. T. A. Comery et al., "Abnormal dendritic spines in fragile X knockout mice: Maturation and pruning deficits," Proc. Nat. Acad. Sci. USA, vol. 94, no. 10, pp. 5401-5404, 1997.
55. M. Passafaro et al., "Induction of dendritic spines by an extracellular domain of AMPA receptor subunit GluR2," Nature, vol. 424, no. 6949, pp. 677-681, 2003.
56. C. Sala et al., "Inhibition of dendritic spine morphogenesis and synaptic transmission by activity-inducible protein Hornerla," J. Neurosci., vol. 23, no. 15, pp. 6327-6337, 2003.
57. A. Majewska, A. Tashiro, and R. Yuste, "Regulation of spine calcium dynamics by rapid spine motility," J. Neurosci., vol. 20, no. 22, pp. 8262-8268, 2000.
58. M. E. Dailey and S. J. Smith, "The dynamics of dendritic structure in developing hippocampal slices," J. Neurosci., vol. 16, pp. 2983-2994, 1996.
59. E. A. Nimchinsky, A. M. Oberlander, and K. Svoboda, "Abnormal development of dendritic spines in FMRl knock-out mice," J. Neurosci., vol. 21, no. 14, pp. 5139-5146, 2001.
60. Y. Ji et al., "Apolipoprotein E isoform-specific regulation of dendritic spine morphology in apolipoprotein E transgenic mice and Alzheimer's disease patients," Neuroscience, vol. 122, no. 2, pp. 305-315, 2003.
61. J. Young and S. Povey, "The genetic basis of tuberous sclerosis," Mol. Med. Today, vol. 4, no. 7, pp. 313-319, 1998.
62. M. R. Gomez, "Phenotypes of the tuberous sclerosis complex with a revision of diagnostic criteria," Ann. New York Acad. Sci., vol. 615, pp. 1-7, 1991.
63. M. van Slegtenhorst et al., "Identification of the tuberous sclerosis gene TSC1 on chromosome 9q34," Science, vol. 277, no. 5327, pp. 805-808, 1997.
64. Consortium, "Identification and characterization of the tuberous sclerosis gene on chromosome 16: The European Chromosome 16 Tuberous Sclerosis Consortium," Cell, vol. 75, no. 7, pp. 1305-1315, 1993.
65. M. M. Maheshwar et al., "The GAP-related domain of tuberin, the product of the TSC2 gene, is a target for missense mutations in tuberous sclerosis," Human Mol. Genetics, vol. 6, no. 11, pp. 1991-1996, 1997.
66. H. Onda et al., "Tsc2(+/-) mice develop tumors in multiple sites that express gelsolin and are influenced by genetic background," J. Clin. Invest., vol. 104, no. 6, pp. 687-695, 1999.
67. K. S. Au et al., "Germ-line mutational analysis of the TSC2 gene in 90 tuberous-sclerosis patients," Amer. J. Human Genetics, vol. 62, no. 2, pp. 286-294, 1998.
68. T. Kobayashi et al., "A germ-line Tsc1 mutation causes tumor development and embryonic lethality that are similar, but not identical to, those caused by Tsc2 mutation in mice," Proc. Nat. Acad. Sci. USA, vol. 98, no. 15, pp. 8762-8767, 2001.
69. S. C. Kozma and G. Thomas, "Regulation of cell size in growth, development and human disease: PI3K, PKB and S6K," Bioessays, vol. 24, no. 1, pp. 65-71, 2002.
70. H. Stocker and E. Hafen, "Genetic control of cell size," Curr. Opin. Genetics Dev., vol. 10, no. 5, pp. 529-535, 2000.
71. C. J. Potter, L. G. Pedraza, and T. Xu, "Akt regulates growth by directly phosphorylating Tsc2," Nature Cell. Biol., vol. 4, no. 9, pp. 658-665, 2002.
72. W. Denk and K. Svoboda, "Photon upmanship: Why multiphoton imaging is more than a gimmick," Neuron, vol. 18, pp. 351-357, 1997.
73. L. Stoppini, P. A. Buchs, and D. A. Muller, "A simple method for organotypic cultures of nervous tissue," J. Neurosci. Meth., vol. 37, pp. 173-182, 1991.
74. D. C. Lo, A. K. McAllister, and L. C. Katz, "Neuronal transfection in brain slices using particle-mediated gene transfer," Neuron, vol. 13, pp. 1263-1268, 1994.
75. G. N. Elston, R. Tweedale, and M. G. Rosa, "Supragranular pyramidal neurones in the medial posterior parietal cortex of the macaque monkey: Morphological heterogeneity in subdivisions of area 7," Neuroreport, vol. 10, no. 9, pp. 1925-1929, 1999.
76. B. Jacobs et al., "Regional dendritic and spine variation in human cerebral cortex: A quantitative golgi study," Cerebr. Cortex, vol. 11, no. 6, pp. 558-571, 2001.
77. E. A. Nimchinsky, B. L. Sabatini, and K. Svoboda, "Structure and function of dendritic spines," Annu. Rev. Physiol., vol. 64, pp. 313-353, 2002.
78. M. Matsuzaki et al., "Structural basis of long-term potentiation in single dendritic spines," Nature, vol. 429, no. 6993, pp. 761-766, 2004.
79. K. Zito et al., "Induction of spine growth and synapse formation by regulation of the spine actin cytoskeleton," Neuron, vol. 44, no. 2, pp. 321-334, 2004.
80. I. Y. Y. Koh et al., "An image analysis algorithm for dendritic spines," Neural Comput., vol. 14, no. 6, pp. 1283-1310, 2002.
81. C. M. Weaver et al., "Automated algorithms for multiscale morphometry of neuronal dendrites," Neural Comput., vol. 16, no. 7, pp. 1353-1383, 2004.
82. B. Zheng, Y. H. Chang, and D. Gur, "Computerized detection of masses in digitized mammograms using single-image segmentation and a multilayer topographic feature analysis," Acad. Radiol., vol. 2, no. 11, pp. 959-966, 1995.
83. S. Shiffman, G. D. Rubin, and S. Napel, "Medical image segmentation using analysis of isolable-contour maps," IEEE Trans. Med. Imag., vol. 19, no. 11, pp. 1064-1074, 2000.
84. Y. Amit, "Graphical shape templates for automatic anatomy detection with applications to MRI brain scans," IEEE Trans. Med. Imag., vol. 16, no. 1, pp. 28-40, 1997.
85. J. Cheng, X. Zhou, E. Miller, R. M. Witt, J. M. Zhu, B. L. Sabatini, and S. T. C. Wong, "A novel computational approach for automatic dendrite spines detection in two-photon laser scan microscopy," J. Neurosci. Meth., vol. 165, no. 1, pp. 122-134, September 15, 2007.
86. X. Zhou, X. Wang, and E. R. Dougherty, "Nonlinear probit gene classification using mutual information and wavelet-based, feature selection," J. Biol. Syst., vol. 12, no. 3, pp. 371-386, 2004.
87. R. Battiti, "Using mutual information for selecting features in supervised neural-net learning," IEEE Trans. Neural Netw., vol. 5, no. 4, pp. 537-550, 1994.
88. X. Zhou et al., "Mutual information-based feature selection in studying perturbation of dendritic structure caused by TSC2 inactivation," Neuroinformatics, vol. 4, no. 1, pp. 81-94, 2006.
89. R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification, 2nd ed. New York: Wiley, 2001.
90. T. M. Cover and J. A. Thomas, Elements of Information Theory, New York: Wiley, 1991.