Main Menu (Mobile)- Block

Main Menu - Block

custom | custom

Search Results

filters_region_cap | custom


facetapi-Q2b17qCsTdECvJIqZJgYMaGsr8vANl1n | block

Associated Lab

facetapi-W9JlIB1X0bjs93n1Alu3wHJQTTgDCBGe | block
facetapi-61yz1V0li8B1bixrCWxdAe2aYiEXdhd0 | block
facetapi-PV5lg7xuz68EAY8eakJzrcmwtdGEnxR0 | block
general_search_page-panel_pane_1 | views_panes

2449 Janelia Publications

Showing 2431-2440 of 2449 results
11/08/07 | Evolution of genes and genomes on the Drosophila phylogeny.
Clark AG, Eisen MB, Smith DR, Bergman CM, Oliver B, Markow TA, Kaufman TC, Kellis M, Gelbart W, Iyer VN, Pollard DA, Sackton TB, Larracuente AM, Singh ND, Abad JP, Abt DN, Adryan B, Aguade M, Akashi H, Anderson WW, Aquadro CF, Ardell DH, Arguello R, Artieri CG, Barbash DA, Barker D, Barsanti P, Batterham P, Batzoglou S, Begun D, Bhutkar A, Blanco E, Bosak SA, Bradley RK, Brand AD, Brent MR, Brooks AN, Brown RH, Butlin RK, Caggese C, Calvi BR, Bernardo de Carvalho A, Caspi A, Castrezana S, Celniker SE, Chang JL, Chapple C, Chatterji S, Chinwalla A, Civetta A, Clifton SW, Comeron JM, Costello JC, Coyne JA, Daub J, David RG, Delcher AL, Delehaunty K, Do CB, Ebling H, Edwards K, Eickbush T, Evans JD, Filipski A, Findeiss S, Freyhult E, Fulton L, Fulton R, Garcia AC, Gardiner A, Garfield DA, Garvin BE, Gibson G, Gilbert D, Gnerre S, Godfrey J, Good R, Gotea V, Gravely B, Greenberg AJ, Griffiths-Jones S, Gross S, Guigo R, Gustafson EA, Haerty W, Hahn MW, Halligan DL, Halpern AL, Halter GM, Han MV, Heger A, Hillier L, Hinrichs AS, Holmes I, Hoskins RA, Hubisz MJ, Hultmark D, Huntley MA, Jaffe DB, Jagadeeshan S, Jeck WR, Johnson J, Jones CD, Jordan WC, Karpen GH, Kataoka E, Keightley PD, Kheradpour P, Kirkness EF, Koerich LB, Kristiansen K, Kudrna D, Kulathinal RJ, Kumar S, Kwok R, Lander E, Langley CH, Lapoint R, Lazzaro BP, Lee S, Levesque L, Li R, Lin C, Lin MF, Lindblad-Toh K, Llopart A, Long M, Low L, Lozovsky E, Lu J, Luo M, Machado CA, Makalowski W, Marzo M, Matsuda M, Matzkin L, McAllister B, McBride CS, McKernan B, McKernan K, Mendez-Lago M, Minx P, Mollenhauer MU, Montooth K, Mount SM, Mu X, Myers E, Negre B, Newfeld S, Nielsen R, Noor MA, O’Grady P, Pachter L, Papaceit M, Parisi MJ, Parisi M, Parts L, Pedersen JS, Pesole G, Phillippy AM, Ponting CP, Pop M, Porcelli D, Powell JR, Prohaska S, Pruitt K, Puig M, Quesneville H, Ram KR, Rand D, Rasmussen MD, Reed LK, Reenan R, Reily A, Remington KA, Rieger TT, Ritchie MG, Robin C, Rogers Y, Rohde C, Rozas J, Rubenfield MJ, Ruiz A, Russo S, Salzberg SL, Sanchez-Gracia A, Saranga DJ, Sato H, Schaeffer SW, Schatz MC, Schlenke T, Schwartz R, Segarra C, Singh RS, Sirot L, Sirota M, Sisneros NB, Smith CD, Smith TF, Spieth J, Stage DE, Stark A, Stephan W, Strausberg RL, Strempel S, Sturgill D, Sutton G, Sutton GG, Tao W, Teichmann S, Tobari YN, Tomimura Y, Tsolas JM, Valente VL, Venter E, Venter JC, Vicario S, Vieira FG, Vilella AJ, Villasante A, Walenz B, Wang J, Wasserman M, Watts T, Wilson D, Wilson RK, Wing RA, Wolfner MF, Wong A, Wong GK, Wu C, Wu G, Yamamoto D, Yang H, Yang S, Yorke JA, Yoshida K, Zdobnov E, Zhang P, Zhang Y, Zimin AV, Baldwin J, Abdouelleil A, Abdulkadir J, Abebe A, Abera B, Abreu J, Acer SC, Aftuck L, Alexander A, An P, Anderson E, Anderson S, Arachi H, Azer M, Bachantsang P, Barry A, Bayul T, Berlin A, Bessette D, Bloom T, Blye J, Boguslavskiy L, Bonnet C, Boukhgalter B, Bourzgui I, Brown A, Cahill P, Channer S, Cheshatsang Y, Chuda L, Citroen M, Collymore A, Cooke P, Costello M, D’Aco K, Daza R, De Haan G, DeGray S, DeMaso C, Dhargay N, Dooley K, Dooley E, Doricent M, Dorje P, Dorjee K, Dupes A, Elong R, Falk J, Farina A, Faro S, Ferguson D, Fisher S, Foley CD, Franke A, Friedrich D, Gadbois L, Gearin G, Gearin CR, Giannoukos G, Goode T, Graham J, Grandbois E, Grewal S, Gyaltsen K, Hafez N, Hagos B, Hall J, Henson C, Hollinger A, Honan T, Huard MD, Hughes L, Hurhula B, Husby ME, Kamat A, Kanga B, Kashin S, Khazanovich D, Kisner P, Lance K, Lara M, Lee W, Lennon N, Letendre F, LeVine R, Lipovsky A, Liu X, Liu J, Liu S, Lokyitsang T, Lokyitsang Y, Lubonja R, Lui A, MacDonald P, Magnisalis V, Maru K, Matthews C, McCusker W, McDonough S, Mehta T, Meldrim J, Meneus L, Mihai O, Mihalev A, Mihova T, Mittelman R, Mlenga V, Montmayeur A, Mulrain L, Navidi A, Naylor J, Negash T, Nguyen T, Nguyen N, Nicol R, Norbu C, Norbu N, Novod N, O’Neill B, Osman S, Markiewicz E, Oyono OL, Patti C, Phunkhang P, Pierre F, Priest M, Raghuraman S, Rege F, Reyes R, Rise C, Rogov P, Ross K, Ryan E, Settipalli S, Shea T, Sherpa N, Shi L, Shih D, Sparrow T, Spaulding J, Stalker J, Stange-Thomann N, Stavropoulos S, Stone C, Strader C, Tesfaye S, Thomson T, Thoulutsang Y, Thoulutsang D, Topham K, Topping I, Tsamla T, Vassiliev H, Vo A, Wangchuk T, Wangdi T, Weiand M, Wilkinson J, Wilson A, Yadav S, Young G, Yu Q, Zembek L, Zhong D, Zimmer A, Zwirko Z, Jaffe DB, Alvarez P, Brockman W, Butler J, Chin C, Gnerre S, Grabherr M, Kleber M, Mauceli E, MacCallum I
Nature. 2007 Nov 8;450:203-18. doi: 10.1038/nature06341

Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.

View Publication Page
10/23/07 | Dendritic spikes induce single-burst long-term potentiation.
Remy S, Spruston N
Proceedings of the National Academy of Sciences of the United States of America. 2007 Oct 23;104(43):17192-7. doi: 10.1073/pnas.0707919104

The hippocampus is essential for episodic memory, which requires single-trial learning. Although long-term potentiation (LTP) of synaptic strength is a candidate mechanism for learning, it is typically induced by using repeated synaptic activation to produce precisely timed, high-frequency, or rhythmic firing. Here we show that hippocampal synapses potentiate robustly in response to strong activation by a single burst. The induction mechanism of this single-burst LTP requires activation of NMDA receptors, L-type voltage-gated calcium channels, and dendritic spikes. Thus, dendritic spikes are a critical trigger for a form of LTP that is consistent with the function of the hippocampus in episodic memory.

View Publication Page
10/01/07 | Rapidly inducible, genetically targeted inactivation of neural and synaptic activity in vivo.
Tervo D, Karpova AY
Current Opinion in Neurobiology. 2007 Oct;17(5):581-6. doi: 10.1016/j.conb.2007.10.002

Inducible and reversible perturbation of the activity of selected neurons in vivo is critical to understanding the dynamics of brain circuits. Several genetically encoded systems for rapid inducible neuronal silencing have been developed in the past few years offering an arsenal of tools for in vivo experiments. Some systems are based on ion-channels or pumps, others on G protein coupled receptors, and yet others on modified presynaptic proteins. Inducers range from light to small molecules to peptides. This diversity results in differences in the various parameters that may determine the applicability of each tool to a particular biological question. Although further development would be beneficial, the current silencing tool kit already provides the ability to make specific perturbations of circuit function in behaving animals.

View Publication Page
07/23/07 | Global analysis of patterns of gene expression during Drosophila embryogenesis.
Tomancak P, Berman BP, Beaton A, Weiszmann R, Kwan E, Hartenstein V, Celniker SE, Rubin GM
Genome Biology. 2007 July 23;8(7):R145. doi: 10.1186/gb-2007-8-7-r145

Cell and tissue specific gene expression is a defining feature of embryonic development in multi-cellular organisms. However, the range of gene expression patterns, the extent of the correlation of expression with function, and the classes of genes whose spatial expression are tightly regulated have been unclear due to the lack of an unbiased, genome-wide survey of gene expression patterns.

View Publication Page
07/10/07 | Automatic image analysis for gene expression patterns of fly embryos.
Peng H, Long F, Zhou J, Leung G, Eisen MB, Myers EW
BMC Cell Biology. 2007 Jul 10;8(Supplement 1):S7. doi: 10.1007/s12021-010-9090-x

Staining the mRNA of a gene via in situ hybridization (ISH) during the development of a D. melanogaster embryo delivers the detailed spatio-temporal pattern of expression of the gene. Many biological problems such as the detection of co-expressed genes, co-regulated genes, and transcription factor binding motifs rely heavily on the analyses of these image patterns. The increasing availability of ISH image data motivates the development of automated computational approaches to the analysis of gene expression patterns.

View Publication Page
Svoboda Lab
07/10/07 | The functional microarchitecture of the mouse barrel cortex.
Sato TR, Gray NW, Mainen ZF, Svoboda K
PLoS Biology. 2007 Jul 10;5(7):e189. doi: 10.1371/journal.pbio.0050189

Cortical maps, consisting of orderly arrangements of functional columns, are a hallmark of the organization of the cerebral cortex. However, the microorganization of cortical maps at the level of single neurons is not known, mainly because of the limitations of available mapping techniques. Here, we used bulk loading of Ca(2+) indicators combined with two-photon microscopy to image the activity of multiple single neurons in layer (L) 2/3 of the mouse barrel cortex in vivo. We developed methods that reliably detect single action potentials in approximately half of the imaged neurons in L2/3. This allowed us to measure the spiking probability following whisker deflection and thus map the whisker selectivity for multiple neurons with known spatial relationships. At the level of neuronal populations, the whisker map varied smoothly across the surface of the cortex, within and between the barrels. However, the whisker selectivity of individual neurons recorded simultaneously differed greatly, even for nearest neighbors. Trial-to-trial correlations between pairs of neurons were high over distances spanning multiple cortical columns. Our data suggest that the response properties of individual neurons are shaped by highly specific subcolumnar circuits and the momentary intrinsic state of the neocortex.

View Publication Page
06/19/07 | Data-driven decomposition for multi-class classification.
Zhou J, Peng H, Suen CY
Pattern Recognition. 2007 Jun 19;41:67-76. doi: 10.1016/j.patcog.2007.05.020

This paper presents a new study on a method of designing a multi-class classifier: Data-driven Error Correcting Output Coding (DECOC). DECOC is based on the principle of Error Correcting Output Coding (ECOC), which uses a code matrix to decompose a multi-class problem into multiple binary problems. ECOC for multi-class classification hinges on the design of the code matrix. We propose to explore the distribution of data classes and optimize both the composition and the number of base learners to design an effective and compact code matrix. Two real world applications are studied: (1) the holistic recognition (i.e., recognition without segmentation) of touching handwritten numeral pairs and (2) the classification of cancer tissue types based on microarray gene expression data. The results show that the proposed DECOC is able to deliver competitive accuracy compared with other ECOC methods, using parsimonious base learners than the pairwise coupling (one-vs-one) decomposition scheme. With a rejection scheme defined by a simple robustness measure, high reliabilities of around 98% are achieved in both applications.

View Publication Page
05/15/07 | Dendritic D-type potassium currents inhibit the spike afterdepolarization in rat hippocampal CA1 pyramidal neurons.
Metz AE, Spruston N, Martina M
The Journal of Physiology. 2007 May 15;581(Pt 1):175-87. doi: 10.1113/jphysiol.2006.127068

In CA1 pyramidal neurons, burst firing is correlated with hippocampally dependent behaviours and modulation of synaptic strength. One of the mechanisms underlying burst firing in these cells is the afterdepolarization (ADP) that follows each action potential. Previous work has shown that the ADP results from the interaction of several depolarizing and hyperpolarizing conductances located in the soma and the dendrites. By using patch-clamp recordings from acute rat hippocampal slices we show that D-type potassium current modulates the size of the ADP and the bursting of CA1 pyramidal neurons. Sensitivity to alpha-dendrotoxin suggests that Kv1-containing potassium channels mediate this current. Dual somato-dendritic recording, outside-out dendritic recordings, and focal application of dendrotoxin together indicate that the channels mediating this current are located in the apical dendrites. Thus, our data present evidence for a dendritic segregation of Kv1-like channels in CA1 pyramidal neurons and identify a novel action for these channels, showing that they inhibit action potential bursting by restricting the size of the ADP.

View Publication Page
Svoboda Lab
05/01/07 | Channelrhodopsin-2-assisted circuit mapping of long-range callosal projections.
Petreanu L, Huber D, Sobczyk A, Svoboda K
Nature Neuroscience. 2007 May;10:663-8. doi: 10.1038/nn1891

The functions of cortical areas depend on their inputs and outputs, but the detailed circuits made by long-range projections are unknown. We show that the light-gated channel channelrhodopsin-2 (ChR2) is delivered to axons in pyramidal neurons in vivo. In brain slices from ChR2-expressing mice, photostimulation of ChR2-positive axons can be transduced reliably into single action potentials. Combining photostimulation with whole-cell recordings of synaptic currents makes it possible to map circuits between presynaptic neurons, defined by ChR2 expression, and postsynaptic neurons, defined by targeted patching. We applied this technique, ChR2-assisted circuit mapping (CRACM), to map long-range callosal projections from layer (L) 2/3 of the somatosensory cortex. L2/3 axons connect with neurons in L5, L2/3 and L6, but not L4, in both ipsilateral and contralateral cortex. In both hemispheres the L2/3-to-L5 projection is stronger than the L2/3-to-L2/3 projection. Our results suggest that laminar specificity may be identical for local and long-range cortical projections.

View Publication Page
05/01/07 | Flies at the farm: Drosophila at Janelia.
Moses K
Fly. 2007 May-Jun;1(3):139-41

On August 1, 2006 the Howard Hughes Medical Institute's first stand-alone research campus opened at Janelia Farm, near Washington DC. Our mission at Janelia is to do exceptional fundamental research. Our two scientific foci are to understand the function of neural circuits and to develop synergistic imaging technologies. To achieve this we have changed many of the conventions of academic and/or industrial science. The founding director at Janelia is the well-known Drosophilist Gerry Rubin, who has been a central figure in fly molecular, developmental and genomic biology in recent decades. Not coincidentally, we at Janelia fully appreciate the potential of flies to contribute to an understanding of neuronal circuits. Our objectives are ambitious, and in the first ten months of operations at Janelia we have made some good beginnings.

View Publication Page