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Institution

University of California

EducationOakland, California, United States
About: University of California is a education organization based out in Oakland, California, United States. It is known for research contribution in the topics: Population & Layer (electronics). The organization has 55175 authors who have published 52933 publications receiving 1491169 citations. The organization is also known as: UC & University of California System.


Papers
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Journal ArticleDOI
TL;DR: A high-quality reference genome sequence for foxtail millet (Setaria italica) is generated and regions of differential single-nucleotide polymorphism density, distribution of transposable elements, small RNA content, chromosomal rearrangement and segregation distortion are identified.
Abstract: We generated a high-quality reference genome sequence for foxtail millet (Setaria italica). The ~400-Mb assembly covers ~80% of the genome and >95% of the gene space. The assembly was anchored to a 992-locus genetic map and was annotated by comparison with >1.3 million expressed sequence tag reads. We produced more than 580 million RNA-Seq reads to facilitate expression analyses. We also sequenced Setaria viridis, the ancestral wild relative of S. italica, and identified regions of differential single-nucleotide polymorphism density, distribution of transposable elements, small RNA content, chromosomal rearrangement and segregation distortion. The genus Setaria includes natural and cultivated species that demonstrate a wide capacity for adaptation. The genetic basis of this adaptation was investigated by comparing five sequenced grass genomes. We also used the diploid Setaria genome to evaluate the ongoing genome assembly of a related polyploid, switchgrass (Panicum virgatum).

758 citations

Journal ArticleDOI
TL;DR: In this article, 11 passes of the ISEE satellites through the frontside terrestrial magnetopause were identified, where the plasma velocity in the magnetic field and boundary layer was substantially larger than in the magnetosheath, with a view to determining whether the velocity enhancements can be explained by magnetic field reconnection.
Abstract: Eleven passes of the ISEE satellites through the frontside terrestrial magnetopause were identified, where the plasma velocity in the magnetopause and boundary layer was substantially larger than in the magnetosheath. The nature of the plasma flow, magnetic field, and energetic particle fluxes in these regions were examined, with a view to determining whether the velocity enhancements can be explained by magnetic field reconnection.

756 citations

Journal ArticleDOI
10 Dec 2008-Nature
TL;DR: Society must respond to the growing demand for cognitive enhancement by rejecting the idea that 'enhancement' is a dirty word, argue Henry Greely and colleagues.
Abstract: Society must respond to the growing demand for cognitive enhancement. That response must start by rejecting the idea that 'enhancement' is a dirty word, argue Henry Greely and colleagues.

753 citations

Book ChapterDOI
TL;DR: In this article, the authors compare models that use normal and log-normal distributions for coefficients with models using these distributions for WTP (called models in WTP space), and find that the models in preference space fit the data better but provide less reasonable distributions of WTP than the models of preference space.
Abstract: In models with unobserved taste heterogeneity, distributional assumptions can be placed in two ways: (1) by specifying the distribution of coefficients in the utility function and deriving the distribution of willingness to pay (WTP), or (2) by specifying the distribution of WTP and deriving the distribution of coefficients. In general the two approaches are equivalent, in that any mutually compatible distributions for coefficients and WTP can be represented in either way. However, in practice, convenient distributions, such as normal or log-normal, are usually specified, and these convenient distributions have different implications when placed on WTP’s than on coefficients. We compare models that use normal and log-normal distributions for coefficients (called models in preference space) with models using these distributions for WTP (called models in WTP space). We find that the models in preference space fit the data better but provide less reasonable distributions of WTP than the models in WTP space. Our findings suggests that further work is needed to identify distributions that either fit better when applied in WTP space or imply more reasonable distributions of WTP when applied in preference space.

750 citations

Journal ArticleDOI
TL;DR: The fluvial system is a major concern in modeling landform evolution in response to tectonic deformation as discussed by the authors, and sediment routing through alluvial channels must account for supply from slope erosion, transport rates, abrasion, and sorting.
Abstract: The fluvial system is a major concern in modeling landform evolution in response to tectonic deformation. Three stream bed types (bedrock, coarse-bed alluvial, and fine-bed alluvial) differ in factors controlling their occurrence and evolution and in appropriate modeling approaches. Spatial and temporal transitions among bed types occur in response to changes in sediment characteristics and tectonic deformation. Erosion in bedrock channels depends upon the ability to scour or pluck bed material; this detachment capacity is often a power function of drainage area and gradient. Exposure of bedrock in channel beds, due to rapid downcutting or resistant rock, slows the response of headwater catchments to downstream baselevel changes. Sediment routing through alluvial channels must account for supply from slope erosion, transport rates, abrasion, and sorting. In regional landform modeling, implicit rate laws must be developed for sediment production from erosion of sub-grid-scale slopes and small channels.

744 citations


Authors

Showing all 55232 results

NameH-indexPapersCitations
Meir J. Stampfer2771414283776
George M. Whitesides2401739269833
Michael Karin236704226485
Fred H. Gage216967185732
Rob Knight2011061253207
Martin White1962038232387
Simon D. M. White189795231645
Scott M. Grundy187841231821
Peidong Yang183562144351
Patrick O. Brown183755200985
Michael G. Rosenfeld178504107707
George M. Church172900120514
David Haussler172488224960
Yang Yang1712644153049
Alan J. Heeger171913147492
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202322
2022105
2021775
20201,069
20191,225
20181,684