A. Gordon, A. Colman-lerner, T. Chin, K. Benjamin, R. Yu et al., Single-cell quantification of molecules and rates using open-source microscope-based cytometry, Nature Methods, vol.69, issue.2, pp.175-181, 1008.
DOI : 10.1042/bj0690110

M. Kvarnström, K. Logg, A. Diez, K. Bodvard, and M. Käll, Image analysis algorithms for cell contour recognition in budding yeast, Optics Express, vol.16, issue.17, pp.12943-12957, 2008.
DOI : 10.1364/OE.16.012943

M. Tscherepanow, F. Zöllner, M. Hillebrand, and F. Kummert, Automatic segmentation of unstained living cells in bright-field microscope images In Advances in mass data analysis of images and signals in medicine, biotechnology, chemistry and food industry, pp.158-172, 2008.

C. Du, M. M. Spiller, D. White, M. Bretschneider, and T. , 2010 Interactive segmentation of clustered cells via geodesic commute distance and constrained density weighted nystrm method, Cytometry Part A, vol.77, pp.1137-1147, 20993.

Q. Wang, J. Niemi, C. Tan, L. You, and M. West, 2010 Image segmentation and dynamic lineage analysis in single-cell fluorescence microscopy, Cytometry Part A, vol.77

K. Bredies and H. Wolinski, An active-contour based algorithm for the automated segmentation of dense yeast populations on transmission microscopy images, Computing and Visualization in Science, vol.7, issue.3, pp.341-352
DOI : 10.1109/83.661186

L. Brocca, R. Menolascina, F. Di-bernardo, D. Sansone, and C. , 2011 Segmentation, tracking and lineage analysis of yeast cells in bright field microscopy images, In First Int. Workshop on Pattern Recognition in Proteomics Structural Biology and Bioinformatics, pp.131-139

S. Pelet, R. Dechant, S. Lee, F. Peter, and M. , An integrated image analysis platform to quantify signal transduction in single cells, Integrative Biology, vol.9, issue.10, pp.1274-1282, 220139.
DOI : 10.1101/gad.9.13.1559

A. Doncic, U. Eser, O. Atay, and J. Skotheim, 2013 An algorithm to automate yeast segmentation and tracking, PLoS ONE, vol.8
DOI : 10.1371/journal.pone.0057970
URL : http://doi.org/10.1371/journal.pone.0057970

J. Peng, Y. Chen, M. Green, S. Sabatinos, S. Forsburg et al., 2013 PombeX: robust cell segmentation for fission yeast transillumination images, PLoS ONE, vol.8
DOI : 10.1371/journal.pone.0081434
URL : http://doi.org/10.1371/journal.pone.0081434

S. Dimopoulos, C. Mayer, R. F. Stelling, and J. , Accurate cell segmentation in microscopy images using membrane patterns, Bioinformatics, vol.30, issue.18, pp.2644-2651
DOI : 10.1093/bioinformatics/btu302

A. Kuijper, B. Heise, Y. Zhou, L. He, W. Heds et al., 2014 Segmentation of clustered cells in microscopy images by geometric PDEs and level sets, Handbook of biomedical imaging, pp.475-487

C. Zhang, F. Huber, M. Knop, and F. Hamprecht, 2014 Yeast cell detection and segmentation in bright field microscopy, IEEE 11th Int. Symp. Biomedical Imaging (ISBI), pp.1267-1270
DOI : 10.1109/isbi.2014.6868107
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.646.5300

E. Meijering, Cell Segmentation: 50 Years Down the Road [Life Sciences], IEEE Signal Processing Magazine, vol.29, issue.5, pp.140-145, 2012.
DOI : 10.1109/MSP.2012.2204190

T. Jones, A. Carpenter, and P. Golland, Voronoibased segmentation of cells on image manifolds, ICCV Workshop on Computer Vision for Biomedical Image Applications, pp.535-543, 2005.

F. Meyer, Topographic distance and watershed lines. Signal Process, pp.113-125, 1994.
DOI : 10.1016/0165-1684(94)90060-4

M. Kass, A. Witkin, and D. Terzopoulos, Snakes: Active contour models, International Journal of Computer Vision, vol.5, issue.6035, pp.321-331, 1988.
DOI : 10.1007/BF00133570
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.124.5318

E. Meijering, O. Dzyubachyk, and I. Smal, Methods for Cell and Particle Tracking, Methods in Enzymology, vol.504, pp.183-200
DOI : 10.1016/B978-0-12-391857-4.00009-4

J. Denzler and H. Niemann, Active Rays: Polar-transformed Active Contours for Real-Time Contour Tracking, Real-Time Imaging, vol.5, issue.3, pp.203-213, 1999.
DOI : 10.1006/rtim.1997.0116
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.49.2762

R. Delgado-gonzalo, N. Denervaud, S. Maerkl, and M. Unser, 2010 Multi-target tracking of packed yeast cells, 7th IEEE Int. Symp. Biomedical Imaging: From Nano to Macro, pp.544-547

J. Uhlendorf, A. Miermont, T. Delaveau, G. Charvin, F. Fages et al., 2012 Longterm model predictive control of gene expression at the population and single-cell levels, Proc. Natl Acad. Sci. USA 109 CellProfiler: image analysis software for identifying and quantifying cell phenotypes, pp.271-285, 2006.

F. De-chaumont, Icy: an open bioimage informatics platform for extended reproducible research, Nature Methods, vol.9, issue.7, pp.690-696, 2075.
DOI : 10.1038/nmeth.1924

J. Munkres, Algorithms for the Assignment and Transportation Problems, Journal of the Society for Industrial and Applied Mathematics, vol.5, issue.1, pp.32-38, 1957.
DOI : 10.1137/0105003
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.228.3911

M. Winter, W. Mankowski, E. Wait, S. Temple, and A. Cohen, 2016 LEVER: software tools for segmentation, tracking and lineaging of proliferating cells, Bioinformatics, vol.32, pp.3530-3531

S. Chen, T. Zhao, G. Gordon, and R. Murphy, 2006 A novel graphical model approach to segmenting cell images, IEEE Symp, pp.28-29
DOI : 10.1109/cibcb.2006.330975
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.62.4112

M. Ma?ka, A benchmark for comparison of cell tracking algorithms, Bioinformatics, vol.30, issue.11, pp.1609-1617
DOI : 10.1093/bioinformatics/btu080

A. Llamosi, A. Gonzalez-vargas, C. Versari, E. Cinquemani, G. Ferrari-trecate et al., What Population Reveals about Individual Cell Identity: Single-Cell Parameter Estimation of Models of Gene Expression in Yeast, PLOS Computational Biology, vol.10, issue.2, p.1004706
DOI : 10.1371/journal.pcbi.1004706.s011
URL : https://hal.archives-ouvertes.fr/hal-01248298

A. Sigal, Variability and memory of protein levels in human cells, Nature, vol.22, issue.7119, pp.643-646, 2006.
DOI : 10.1038/nature05316

A. Carpenter, L. Kamentsky, and K. Eliceiri, 2012 A call for bioimaging software usability, Nat. Methods J. R. Soc. Interface, vol.9, issue.14, pp.666-670
DOI : 10.1038/nmeth.2073
URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3641581