@article {65972,
	title = {High throughput instrument to screen fluorescent proteins under two-photon excitation.},
	journal = {Biomedical Optics Express},
	volume = {11},
	year = {2020},
	month = {2020 Dec 01},
	pages = {7192-7203},
	abstract = {<p>Two-photon microscopy together with fluorescent proteins and fluorescent protein-based biosensors are commonly used tools in neuroscience. To enhance their experimental scope, it is important to optimize fluorescent proteins for two-photon excitation. Directed evolution of fluorescent proteins under one-photon excitation is common, but many one-photon properties do not correlate with two-photon properties. A simple system for expressing fluorescent protein mutants is colonies on an agar plate. The small focal volume of two-photon excitation makes creating a high throughput screen in this system a challenge for a conventional point-scanning approach. We present an instrument and accompanying software that solves this challenge by selectively scanning each colony based on a colony map captured under one-photon excitation. This instrument, called the GIZMO, can measure the two-photon excited fluorescence of 10,000 colonies in 7 hours. We show that the GIZMO can be used to evolve a fluorescent protein under two-photon excitation.</p>
},
	issn = {2156-7085},
	doi = {10.1364/BOE.409353},
	author = {Molina, Rosana S and King, Jonathan and Franklin, Jacob and Clack, Nathan and McRaven, Christopher and Goncharov, Vasily and Flickinger, Daniel and Svoboda, Karel and Drobizhev, Mikhail and Hughes, Thomas E}
}
@article {2700,
	title = {Automated reconstruction of neuronal morphology based on local geometrical and global structural models.},
	journal = {Neuroinformatics},
	volume = {9},
	year = {2011},
	month = {2011 May 6},
	pages = {247-61},
	abstract = {<p>Digital reconstruction of neurons from microscope images is an important and challenging problem in neuroscience. In this paper, we propose a model-based method to tackle this problem. We first formulate a model structure, then develop an algorithm for computing it by carefully taking into account morphological characteristics of neurons, as well as the image properties under typical imaging protocols. The method has been tested on the data sets used in the DIADEM competition and produced promising results for four out of the five data sets.</p>
},
	issn = {1559-0089},
	doi = {10.1007/s12021-011-9120-3},
	author = {Zhao, Ting and Xie, Jun and Amat, Fernando and Clack, Nathan and Ahammad, Parvez and Peng, Hanchuan and Long, Fuhui and Myers, Eugene}
}
