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Neuroinformatics
Erschienen in: Neuroinformatics 1/2015

01.01.2015 | News Item

Doubling up on the Fly: NeuroMorpho.Org Meets Big Data

verfasst von: Sumit Nanda, M. Mowafak Allaham, Maurizio Bergamino, Sridevi Polavaram, Rubén Armañanzas, Giorgio A. Ascoli, Ruchi Parekh

Erschienen in: Neuroinformatics | Ausgabe 1/2015

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Excerpt

NeuroMorpho.Org (RRID:nif-0000-00006) is a centralized repository of neuronal reconstructions hosting data from a variety of species, brain regions, and experimental conditions.1 This resource aims to provide dense coverage of available data by including all digital tracings described in peer-reviewed publications that the authors are willing to share.2 Although most reconstructions to date are acquired manually or semi-manually,3 the transition to quasi-automated methods is widely considered as necessary for long-term progress.4 The 2010 DIADEM competition (DiademChallenge.org, RRID:nif-0000-23194) helped foster considerable advances towards tracing automation5 and was followed one year later by the large-scale reconstruction of more than 16,000 Drosophila neurons.6 The public posting of all image stacks and corresponding digital tracings on flycircuit.tw after an additional year7 constituted the first (and so far only) success in high-throughput digital morphology. …
Vorheriger Artikel A Digital Atlas of Ion Channel Expression Patterns in the Two-Week-Old Rat Brain

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Fußnoten
1
Ascoli, G.A., Donohue, D.E., Halavi, M. (2007). NeuroMorpho.Org—A central resource for neuronal morphologies. Journal of Neuroscience, 27,9247–9251.
 
2
Halavi, M., Polavaram, S., Donohue, D.E., Hamilton, G., Hoyt, J., Smith, K., Ascoli, G.A. (2008). NeuroMorpho.Org implementation of digital neuroscience: dense coverage and integration with the NIF. Neuroinformatics 6, 241–252.
 
3
Halavi, M., Hamilton, K.A., Parekh, R., Ascoli, G.A. (2012). Digital reconstructions of neuronal morphology: three decades of research trends. Front Neuroscience 6, 49. doi: 10.​3389/​fnins.​2012.​00049.
 
4
Svoboda, K. (2011). The past, present, and future of single neuron reconstruction. Neuroinformatics 9, 97–98.
 
5
Liu, Y. (2011) The DIADEM and beyond. Neuroinformatics 9, 99–102.
 
6
Chiang, A.S., Lin, C.Y., Chuang, C.C., Chang, H.M., Hsieh, C.H., Yeh, C.W., Shih, C.T., Wu, J.J., Wang, G.T., Chen, Y.C., Wu, C.C., Chen, G.Y., Ching, Y.T., Lee, P.C., Lin, C.Y., Lin, H.H., Wu, C.C., Hsu, H.W., Huang, Y.A., Chen, J.Y., Chiang, H.J., Lu, C.F., Ni, R.F., Yeh, C.Y., Hwang, J.K. (2011). Three-dimensional reconstruction of brain-wide wiring networks in Drosophila at single-cell resolution. Current Biology 21, 1–11.
 
7
Lee, P.C., Chuang, C.C., Chiang, A.S., Ching, Y.T. (2012) High-throughput computer method for 3D neuronal structure reconstruction from the image stack of the Drosophila brain and its applications. PLoS Computing Biology 8(9), e1002658. doi: 10.​1371/​journal.​pcbi.​1002658.
 
8
Costa, M., Ostrovsky, A.D., Manton, J.D., Prohaska, S., Jefferis, G.S. (2014). NBLAST: Rapid, sensitive comparison of neuronal structure and construction of neuron family databases. BioRxiv. doi: 10.​1101/​006346.
 
9
Scorcioni, R., Polavaram, S., Ascoli, G.A. (2008) L-Measure: a web-accessible tool for the analysis, comparison and search of digital reconstructions of neuronal morphologies. Nature Protocols 3, 866–876.
 
10
St. Pierre, S.E., Ponting, L., Stefancsik, R., McQuilton, P., and the FlyBase Consortium (2014). FlyBase 102—advanced approaches to interrogating FlyBase. Nucleic Acids Research 42(D1), D780-D788.
 
11
Xiao, H., Peng, H. (2013). APP2: automatic tracing of 3D neuron morphology based on hierarchical pruning of a gray-weighted image distance-tree. Bioinformatics 29, 1448–1454.
 
12
Rivera-Alba, M., Peng, H., de Polavieja, G.G., Chklovskii, D.B. (2014). Wiring economy can account for cell body placement across species and brain areas. Current Biology 24, R109-R110.
 
13
Milyaev, N., Osumi-Sutherland, D., Reeve, S., Burton, N., Baldock, R.A., Armstrong, J.D. (2012). The Virtual Fly Brain browser and query interface. Bioinformatics 28, 411–415.
 
14
Parekh, R., Ascoli, G.A. (2013). Neuronal morphology goes digital: a research hub for cellular and system neuroscience. Neuron 77, 1017–1038.
 
15
Parekh, R., Ascoli, G.A. (2014). Quantitative investigations of axonal and dendritic arbors: development, structure, function, and pathology. Neuroscientist.
 
16
Hamad, M.I., Ma-Högemeier, Z.L., Riedel, C., Conrads, C., Veitinger, T., Habijan, T., Schulz, J.N., Krause, M., Wirth, M.J., Hollmann, M., Wahle, P. (2011). Cell class-specific regulation of neocortical dendrite and spine growth by AMPA receptor splice and editing variants. Development 138, 4301–4313.
 
17
Nogueira-Campos, A.A., Finamore, D.M., Imbiriba, L.A., Houzel, J.C., Franca, J.G. (2012). Distribution and morphology of nitrergic neurons across functional domains of the rat primary somatosensory cortex. Front Neural Circuits 6, 57. doi: 10.​3389/​fncir.​2012.​00057.
 
Metadaten
Titel
Doubling up on the Fly: NeuroMorpho.Org Meets Big Data
verfasst von
Sumit Nanda
M. Mowafak Allaham
Maurizio Bergamino
Sridevi Polavaram
Rubén Armañanzas
Giorgio A. Ascoli
Ruchi Parekh
Publikationsdatum
01.01.2015
Verlag
Springer US
Erschienen in
Neuroinformatics / Ausgabe 1/2015
Print ISSN: 1539-2791
Elektronische ISSN: 1559-0089
DOI
https://doi.org/10.1007/s12021-014-9257-y

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