Toward the virtual cell: Automated approaches to building models of subcellular organization "learned" from microscopy images

BioEssays

Volumn 34, Issue 9, 2012, Pages 791-799

  Buck, Taráz E ^a,b   Li, Jieyue ^b,c   Rohde, Gustavo K ^a,b,c   Murphy, Robert F ^a,b,c,d  

^a Carnegie Mellon University ^*  (United States)

^b CARNEGIE MELLON UNIVERSITY   (United States)

^c CARNEGIE MELLON UNIVERSITY   (United States)

^d UNIVERSITY OF FREIBURG   (Germany)

Author keywords

Cell modeling; Cell shape; Generative models; Image analysis; Machine learning

Indexed keywords

TUBULIN;

ARTICLE; AUTOMATION; CELL NUCLEUS; CELL ORGANELLE; CELL SHAPE; CELL STRUCTURE; CELL VACUOLE; CELLULAR PARAMETERS; COMPUTATIONAL FLUID DYNAMICS; HIGH THROUGHPUT SCREENING; HUMAN; IMAGE ANALYSIS; LEARNING; MICROSCOPY; MICROTUBULE; PHENOTYPE; SUBCELLULAR ORGANIZATION; VIRTUAL REALITY;

AUTOMATIC DATA PROCESSING; CELL PHYSIOLOGICAL PROCESSES; CELL SHAPE; CELL SIZE; CELLULAR STRUCTURES; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; HELA CELLS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MICROSCOPY; MODELS, BIOLOGICAL; MOLECULAR CONFORMATION; ORGANELLE SHAPE; ORGANELLE SIZE;

EID: 84865160982     PISSN: 02659247     EISSN: 15211878     Source Type: Journal    
DOI: 10.1002/bies.201200032     Document Type: Article

References (33)

1. Danuser G. 2011. Computer vision in cell biology. Cell 147: 973-8.
2. Shariff A, Kangas J, Coelho LP, Quinn S, et al. 2010. Automated image analysis for high content screening and analysis. J Biomol Screening 15: 726-34.
3. Glory E, Newberg J, Murphy RF. 2008. Automated comparison of protein subcellular location patterns between images of normal and cancerous tissues. Proc IEEE Int Symp Biomed Imaging 2008: 304-7.
4. Sigal A, Milo R, Cohen A, Geva-Zatorsky N, et al. 2006. Dynamic proteomics in individual human cells uncovers widespread cell-cycle dependence of nuclear proteins. Nat Methods 3: 525-31.
5. Shariff A, Murphy RF, Rohde GK. 2010. A generative model of microtubule distributions, and indirect estimation of its parameters from fluorescence microscopy images. Cytometry Part A 77A: 457-66.
6. Shariff A, Murphy RF, Rohde GK. 2011. Automated estimation of microtubule model parameters from 3-d live cell microscopy images. Proc IEEE Int Symp Biomed Imaging 2011: 1330-3.
7. Rohde GK, Ribeiro AJS, Dahl KN, Murphy RF. 2008. Deformation-based nuclear morphometry: capturing nuclear shape variation in HeLa cells. Cytometry Part A 73: 341-50.
8. Peng T, Wang W, Rohde GK, Murphy RF. 2009. Instance-based generative biological shape modeling. Proc IEEE Int Symp Biomed Imaging 2009: 690-3.
9. Pincus Z, Theriot JA. 2007. Comparison of quantitative methods for cell-shape analysis. J Microsc 227: 140-56.
10. Lacayo CI, Pincus Z, VanDuijn MM, Wilson CA, et al. 2007. Emergence of large-scale cell morphology and movement from local actin filament growth dynamics. PLoS Biol 5: e233.
11. Zhao T, Murphy RF. 2007. Automated learning of generative models for subcellular location: building blocks for systems biology. Cytometry Part A 71A: 978-90.
12. Peng T, Murphy RF. 2011. Image-derived, three-dimensional generative models of cellular organization. Cytometry Part A 79A: 383-91.
13. Bakal C, Aach J, Church G, Perrimon N. 2007. Quantitative morphological signatures define local signaling networks regulating cell morphology. Science 316: 1753-6.
14. Barbe L, Lundberg E, Oksvold P, Stenius A, et al. 2008. Toward a confocal subcellular atlas of the human proteome. Mol Cell Proteomics 7: 499-508.
15. Chen X, Velliste M, Murphy RF. 2006. Automated interpretation of subcellular patterns in fluorescence microscope images for location proteomics. Cytometry Part A 69A: 631-40.
16. Newberg J, Murphy RF. 2008. A framework for the automated analysis of subcellular patterns in human protein atlas images. J Proteome Res 7: 2300-8.
17. Hepburn I, Chen W, Wils S, De Schutter E. 2012. Steps: efficient simulation of stochastic reaction-diffusion models in realistic morphologies. BMC Syst Biol 6: 36.
18. Maly VI, Maly IV. 2010. Symmetry, stability, and reversibility properties of idealized confined microtubule cytoskeletons. Biophys J 99: 2831-40.
19. Nadkarni S, Bartol TM, Sejnowski TJ, Levine H. 2010. Modelling vesicular release at hippocampal synapses. PLoS Comput Biol 6: e1000983.
20. Schreiber CH, Stewart M, Duke T. 2010. Simulation of cell motility that reproduces the force-velocity relationship. Proc Natl Acad Sci USA 107: 9141-6.
21. Wang L, Castro CE, Boyce MC. 2011. Growth strain-induced wrinkled membrane morphology of white blood cells. Soft Matter 7: 11319-24.
22. Keren K, Pincus Z, Allen GM, Barnhart EL, et al. 2008. Mechanism of shape determination in motile cells. Nature 453: 475-80.
23. Tyson JJ, Chen K, Novak B. 2001. Network dynamics and cell physiology. Nat Rev Mol Cell Biol 2: 908-16.
24. Boland MV, Murphy RF. 2001. A neural network classifier capable of recognizing the patterns of all major subcellular structures in fluorescence microscope images of hela cells. Bioinformatics 17: 1213-23.
25. Conrad C, Erfle H, Warnat P, Daigle N, et al. 2004. Automatic identification of subcellular phenotypes on human cell arrays. Genome Res 14: 1130-6.
26. Murphy RF. 2010. Communicating subcellular distributions. Cytometry A 77: 686-92.
27. Beg MF, Miller MI, Trouve A, Younes L. 2005. Computing large deformation metric mappings via geodesic flows of diffeomorphisms. Int J Comput Vision 61: 139-57.
28. Danuser G, Waterman-Storer CM. 2006. Quantitative fluorescent speckle microscopy of cytoskeleton dynamics. Annu Rev Biophys Biomol Struct 35: 361-87.
29. Hinow P, Rezania V, Tuszynski JA. 2009. A continuous model for microtubule dynamics with catastrophe, rescue and nucleation processes. Phys Rev E 80: 031904.
30. Hough LE, Schwabe A, Glaser MA, McIntosh JR, et al. 2009. Microtubule depolymerization by the kinesin-8 motor kip3p: a mathematical model. Biophys J 96: 3050-64.
31. Vallotton P, Gupton SL, Waterman-Storer CM, Danuser G. 2004. Simultaneous mapping of filamentous actin flow and turnover in migrating cells by quantitative fluorescent speckle microscopy. Proc Natl Acad Sci USA 101: 9660-5.
32. Zhang R, Brown FLH. 2008. Cytoskeleton mediated effective elastic properties of model red blood cell membranes. J Chem Phys 129: 065101.
33. Brown FLH. 2011. Continuum simulations of biomembrane dynamics and the importance of hydrodynamic effects. Q Rev Biophys 44: 391-432.