@article {48164,
	title = {Active graph matching for automatic joint segmentation and annotation of C. elegans.},
	journal = {Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention},
	volume = {17},
	year = {2014},
	month = {2014},
	pages = {81-8},
	abstract = {<p>In this work we present a novel technique we term active graph matching, which integrates the popular active shape model into a sparse graph matching problem. This way we are able to combine the benefits of a global, statistical deformation model with the benefits of a local deformation model in form of a second-order random field. We present a new iterative energy minimization technique which achieves empirically good results. This enables us to exceed state-of-the art results for the task of annotating nuclei in 3D microscopic images of C. elegans. Furthermore with the help of the generalized Hough transform we are able to jointly segment and annotate a large set of nuclei in a fully automatic fashion for the first time.</p>
},
	keywords = {Algorithms, Animals, Caenorhabditis elegans, Cell Nucleus, Image Enhancement, Image Interpretation, Computer-Assisted, Microscopy, Pattern Recognition, Automated, Reproducibility of Results, Sensitivity and Specificity, Subtraction Technique},
	author = {Kainmueller, Dagmar and Jug, Florian and Rother, Carsten and Myers, Gene}
}
@article {6284,
	title = {Clonal development and organization of the adult Drosophila central brain.},
	journal = {Current biology : CB},
	volume = {23},
	year = {2013},
	month = {2013 Apr 22},
	pages = {633-43},
	abstract = {BACKGROUND: The insect brain can be divided into neuropils that are formed by neurites of both local and remote origin. The complexity of the interconnections obscures how these neuropils are established and interconnected through development. The Drosophila central brain develops from a fixed number of neuroblasts (NBs) that deposit neurons in regional clusters. RESULTS: By determining individual NB clones and pursuing their projections into specific neuropils, we unravel the regional development of the brain neural network. Exhaustive clonal analysis revealed 95 stereotyped neuronal lineages with characteristic cell-body locations and neurite trajectories. Most clones show complex projection patterns, but despite the complexity, neighboring clones often coinnervate the same local neuropil or neuropils and further target a restricted set of distant neuropils. CONCLUSIONS: These observations argue for regional clonal development of both neuropils and neuropil connectivity throughout the Drosophila central brain.},
	issn = {1879-0445},
	doi = {10.1016/j.cub.2013.02.057},
	author = {Yu, Hung-Hsiang and Awasaki, Takeshi and Schroeder, Mark David and Long, Fuhui and Yang, Jacob S and He, Yisheng and Ding, Peng and Kao, Jui-Chun and Wu, Gloria Yueh-Yi and Peng, Hanchuan and Myers, Gene and Lee, Tzumin}
}
@article {2326,
	title = {Error tolerant indexing and alignment of short reads with covering template families.},
	journal = {Journal of Computational Biology: A Journal of Computational Molecular Cell Biology},
	volume = {17},
	year = {2010},
	month = {2010 Oct},
	pages = {1397-1411},
	abstract = {<p>The rapid adoption of high-throughput next generation sequence data in biological research is presenting a major challenge for sequence alignment tools{\textemdash}specifically, the efficient alignment of vast amounts of short reads to large references in the presence of differences arising from sequencing errors and biological sequence variations. To address this challenge, we developed a short read aligner for high-throughput sequencer data that is tolerant of errors or mutations of all types{\textemdash}namely, substitutions, deletions, and insertions. The aligner utilizes a multi-stage approach in which template-based indexing is used to identify candidate regions for alignment with dynamic programming. A template is a pair of gapped seeds, with one used with the read and one used with the reference. In this article, we focus on the development of template families that yield error-tolerant indexing up to a given error-budget. A general algorithm for finding those families is presented, and a recursive construction that creates families with higher error tolerance from ones with a lower error tolerance is developed.</p>
},
	keywords = {Algorithms, Base Sequence, DNA, Genetic, Molecular Sequence Data, Sequence Alignment, Sequence Analysis, Software, Templates},
	issn = {1557-8666},
	doi = {10.1089/cmb.2010.0005},
	author = {Giladi, Eldar and Healy, John and Myers, Gene and Hart, Chris and Kapranov, Philipp and Lipson, Doron and Roels, Steve and Thayer, Edward and Letovsky, Stan}
}
