Hauptseite > Publikationsdatenbank > QPACE: power-efficient parallel architecture based on IBM PowerXCell 8i > print

001     14598
005     20210129210607.0
024 7 _ |2 pmid
|a pmid:16599959
024 7 _ |2 DOI
|a 10.1007/s00450-010-0122-4
037 _ _ |a PreJuSER-14598
041 _ _ |a eng
082 _ _ |a 004
100 1 _ |a Baier, H.
|b 0
|0 P:(DE-HGF)0
245 _ _ |a QPACE: power-efficient parallel architecture based on IBM PowerXCell 8i
260 _ _ |a Berlin
|b Springer
|c 2010
300 _ _ |a
336 7 _ |a Journal Article
|0 PUB:(DE-HGF)16
|2 PUB:(DE-HGF)
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|0 0
|2 EndNote
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a article
|2 DRIVER
440 _ 0 |a Computer Science - Research and Development
|x 1865-2034
|0 23601
|y 3
|v 25
500 _ _ |a Record converted from VDB: 12.11.2012
520 _ _ |a Dawson's burrowing bee is a large, fast-flying solitary nesting bee endemic to the arid zone of Western Australia. In this study the population structure of the species was examined with molecular markers. Using eight microsatellite loci, we genotyped 531 adult female bees collected from 13 populations of Dawson's burrowing bee, Amegilla dawsoni, across the species range. The mean number of alleles per locus ranged from 4 to 38 and expected heterozygosity was uniformly high with a mean of 0.602. Pairwise comparisons of F(ST) among all 13 populations ranged from 0.0071 to 0.0122 with only one significant estimate and an overall F(ST) of 0.001. The entire sample collection was in Hardy-Weinberg equilibrium and there was no evidence of inbreeding with a mean F(IS) of 0.010. The mating and nesting behaviour of this bee suggests that gene flow would be limited by monandry and the fact that almost 90% of females mate immediately on emergence. Nevertheless there is obviously sufficient gene flow to maintain panmixia, and we suggest that this results from infrequent and unreliable rainfall in the species range, which causes the bees to congregate at limited food resources, allowing a small number of unmated females from one emergence site to come into contact with males from another population. In addition, when drought eliminates food resources near an emergence site, the whole population may move elsewhere, increasing gene flow across the species range.
536 _ _ |2 G:(DE-HGF)
|0 G:(DE-Juel1)FUEK411
|x 0
|c FUEK411
|a Scientific Computing (FUEK411)
536 _ _ |a 41G - Supercomputer Facility (POF2-41G21)
|0 G:(DE-HGF)POF2-41G21
|c POF2-41G21
|x 1
|f POF II
588 _ _ |a Dataset connected to Pubmed
650 _ 2 |2 MeSH
|a Alleles
650 _ 2 |2 MeSH
|a Animal Migration
650 _ 2 |2 MeSH
|a Animals
650 _ 2 |2 MeSH
|a Australia
650 _ 2 |2 MeSH
|a Bees: genetics
650 _ 2 |2 MeSH
|a Female
650 _ 2 |2 MeSH
|a Gene Flow
650 _ 2 |2 MeSH
|a Genetic Variation
650 _ 2 |2 MeSH
|a Genotype
650 _ 2 |2 MeSH
|a Geography
650 _ 2 |2 MeSH
|a Heterozygote
650 _ 2 |2 MeSH
|a Microsatellite Repeats: genetics
650 _ 2 |2 MeSH
|a Nesting Behavior
650 _ 2 |2 MeSH
|a Rain
650 _ 2 |2 MeSH
|a Sexual Behavior, Animal
700 1 _ |a Boettiger, H.
|b 1
|0 P:(DE-HGF)0
700 1 _ |a Drochner, M.
|b 2
|0 P:(DE-HGF)0
700 1 _ |a Eicker, N.
|b 3
|u FZJ
|0 P:(DE-Juel1)132090
700 1 _ |a Fischer, U.
|b 4
|0 P:(DE-HGF)0
700 1 _ |a Fodor, Z.
|b 5
|0 P:(DE-HGF)0
700 1 _ |a Frommer, A.
|b 6
|0 P:(DE-HGF)0
700 1 _ |a Gomez, C.
|b 7
|0 P:(DE-HGF)0
700 1 _ |a Goldrian, G.
|b 8
|0 P:(DE-HGF)0
700 1 _ |a Heybrock, S.
|b 9
|0 P:(DE-HGF)0
700 1 _ |a Hierl, D.
|b 10
|0 P:(DE-HGF)0
700 1 _ |a Hüsken, M.
|b 11
|0 P:(DE-HGF)0
700 1 _ |a Huth, T.
|b 12
|0 P:(DE-HGF)0
700 1 _ |a Krill, B.
|b 13
|0 P:(DE-HGF)0
700 1 _ |a Lauritsen, J.
|b 14
|0 P:(DE-HGF)0
700 1 _ |a Lippert, T.
|b 15
|u FZJ
|0 P:(DE-Juel1)132179
700 1 _ |a Maurer, T.
|b 16
|0 P:(DE-HGF)0
700 1 _ |a Mendl, B.
|b 17
|0 P:(DE-HGF)0
700 1 _ |a Meyer, N.
|b 18
|0 P:(DE-HGF)0
700 1 _ |a Nobile, A.
|b 19
|0 P:(DE-HGF)0
700 1 _ |a Ouda, I.
|b 20
|0 P:(DE-HGF)0
700 1 _ |a Pivanti, M.
|b 21
|0 P:(DE-HGF)0
700 1 _ |a Pleiter, D.
|b 22
|0 P:(DE-HGF)0
700 1 _ |a Ries, M.
|b 23
|0 P:(DE-HGF)0
700 1 _ |a Schäfer, A.
|b 24
|0 P:(DE-HGF)0
700 1 _ |a Schick, H.
|b 25
|0 P:(DE-HGF)0
700 1 _ |a Schifano, F.
|b 26
|0 P:(DE-HGF)0
700 1 _ |a Simma, H.
|b 27
|0 P:(DE-HGF)0
700 1 _ |a Solbrig, S.
|b 28
|0 P:(DE-HGF)0
700 1 _ |a Streuer, T.
|b 29
|0 P:(DE-HGF)0
700 1 _ |a Sulanke, K.-H.
|b 30
|0 P:(DE-HGF)0
700 1 _ |a Tripiccione, R.
|b 31
|0 P:(DE-HGF)0
700 1 _ |a Vogt, J.-S.
|b 32
|0 P:(DE-HGF)0
700 1 _ |a Wettig, T.
|b 33
|0 P:(DE-HGF)0
700 1 _ |a Winter, F.
|b 34
|0 P:(DE-HGF)0
773 _ _ |a 10.1007/s00450-010-0122-4
|g Vol. 25
|q 25
|0 PERI:(DE-600)2410154-0
|t Computer science - research and development
|v 25
|y 2010
|x 1865-2034
856 7 _ |u http://dx.doi.org/10.1007/s00450-010-0122-4
909 C O |o oai:juser.fz-juelich.de:14598
|p VDB
913 1 _ |a DE-HGF
|b Schlüsseltechnologien
|l Supercomputing
|1 G:(DE-HGF)POF2-410
|0 G:(DE-HGF)POF2-41G21
|2 G:(DE-HGF)POF2-400
|v Supercomputer Facility
|x 1
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF2
914 1 _ |y 2010
915 _ _ |0 StatID:(DE-HGF)0020
|a No peer review
920 1 _ |k JSC
|l Jülich Supercomputing Centre
|g JSC
|0 I:(DE-Juel1)JSC-20090406
|x 0
970 _ _ |a VDB:(DE-Juel1)126850
980 _ _ |a VDB
980 _ _ |a ConvertedRecord
980 _ _ |a journal
980 _ _ |a I:(DE-Juel1)JSC-20090406
980 _ _ |a UNRESTRICTED

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