Citation guide

Mesmerize provides interfaces to many great tools that were created by other developers. Please cite the papers for the following Viewer Modules and analysis methods that you use in addition to citing Mesmerize. I would also suggest citing numpy, pandas, scipy, sklearn, and matplotlib.

Mesmerize relies heavily on pyqtgraph widgets. Citing pyqtgraph.

Viewer

Module

Cite

CNMF

Giovannucci A., Friedrich J., Gunn P., Kalfon J., Brown, B., Koay S.A., Taxidis J., Najafi F., Gauthier J.L., Zhou P., Baljit, K.S., Tank D.W., Chklovskii D.B., Pnevmatikakis E.A. (2019). CaImAn: An open source tool for scalable Calcium Imaging data Analysis. eLife 8, e38173. https://elifesciences.org/articles/38173
Pnevmatikakis, E.A., Soudry, D., Gao, Y., Machado, T., Merel, J., … & Paninski, L. (2016). Simultaneous denoising, deconvolution, and demixing of calcium imaging data. Neuron 89(2):285-299. http://dx.doi.org/10.1016/j.neuron.2015.11.037
Pnevmatikakis, E.A., Gao, Y., Soudry, D., Pfau, D., Lacefield, C., … & Paninski, L. (2014). A structured matrix factorization framework for large scale calcium imaging data analysis. arXiv preprint arXiv:1409.2903. http://arxiv.org/abs/1409.2903

CNMFE

In addition to the above CNMF papers:
Zhou, P., Resendez, S. L., Rodriguez-Romaguera, J., Jimenez, J. C., Neufeld, S. Q., Giovannucci, A., … Paninski, L. (2018). Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data. ELife, 7. doi: https://doi.org/10.7554/eLife.28728.001

Caiman Motion Correction

Giovannucci A., Friedrich J., Gunn P., Kalfon J., Brown, B., Koay S.A., Taxidis J., Najafi F., Gauthier J.L., Zhou P., Baljit, K.S., Tank D.W., Chklovskii D.B., Pnevmatikakis E.A. (2019). CaImAn: An open source tool for scalable Calcium Imaging data Analysis. eLife 8, e38173. https://elifesciences.org/articles/38173
Pnevmatikakis, E.A., and Giovannucci A. (2017). NoRMCorre: An online algorithm for piecewise rigid motion correction of calcium imaging data. Journal of Neuroscience Methods, 291:83-92. https://doi.org/10.1016/j.jneumeth.2017.07.031

Nodes/Analysis

Node/Method

Cite

k-Shape clustering

Paparrizos, J., & Gravano, L. (2016). k-Shape. ACM SIGMOD Record, 45(1), 69–76. doi: http://dx.doi.org/10.1145/2723372.2737793
Romain Tavenard, Johann Faouzi, Gilles Vandewiele and Felix Divo, Guillaume Androz, Chester Holtz, Marie Payne, Roman Yurchak, Marc Ruβwurm, Kushal Kolar, & Eli Woods. (2017). Tslearn, A Machine Learning Toolkit for Time Series Data. Journal of Machine Learning Research, (118):1−6, 2020. http://jmlr.org/papers/v21/20-091.html

Cross-correlation

Romain Tavenard, Johann Faouzi, Gilles Vandewiele and Felix Divo, Guillaume Androz, Chester Holtz, Marie Payne, Roman Yurchak, Marc Ruβwurm, Kushal Kolar, & Eli Woods. (2017). Tslearn, A Machine Learning Toolkit for Time Series Data. Journal of Machine Learning Research, (118):1−6, 2020. http://jmlr.org/papers/v21/20-091.html

TVDiff Node

Rick Chartrand, “Numerical Differentiation of Noisy, Nonsmooth Data,” ISRN Applied Mathematics, vol. 2011, Article ID 164564, 11 pages, 2011. https://doi.org/10.5402/2011/164564.

Scientific Libraries

Library

numpy

Van Der Walt, S., Colbert, S. C. & Varoquaux, G. The NumPy array: A structure for efficient numerical computation. Comput. Sci. Eng. (2011) doi:10.1109/MCSE.2011.37

pandas

McKinney, W. Data Structures for Statistical Computing in Python. Proc. 9th Python Sci. Conf. (2010)

scipy

Virtanen, P., Gommers, R., Oliphant, T.E. et al. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nat Methods (2020). https://doi.org/10.1038/s41592-019-0686-2

sklearn

Pedregosa, F. et al. Scikit-learn: Machine learning in Python. J. Mach. Learn. Res. (2011)

matplotlib

Hunter, J. D. Matplotlib: A 2D graphics environment. Comput. Sci. Eng. (2007)

pyqtgraph