Institution
Academia Sinica
Facility•Taipei, Taiwan•
About: Academia Sinica is a facility organization based out in Taipei, Taiwan. It is known for research contribution in the topics: Population & Gene. The organization has 52086 authors who have published 65998 publications receiving 1728114 citations. The organization is also known as: Central Research Academy.
Topics: Population, Gene, Galaxy, Catalysis, Large Hadron Collider
Papers published on a yearly basis
Papers
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TL;DR: GCMa was able to regulatesyncytin gene expression via two GCMa-binding sites upstream of the 5′-long terminal repeat of thesyncytin-harboring HERV-W family member in BeWo and JEG3 cells but not in HeLa cells, which may help to explain the mechanism underlying the cell fusion event specific for syncytiotrophoblast formation.
250 citations
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Pohang University of Science and Technology1, Academia Sinica2, Rural Development Administration3, Gyeongsang National University4, Commonwealth Scientific and Industrial Research Organisation5, National University of Singapore6, Huazhong Agricultural University7, University of California, Davis8, International Rice Research Institute9
TL;DR: The aims of this review are to summarize the current status of rice mutant resources, key tools for functional analysis of genes, and the perspectives on how to accelerate rice gene discovery through collaboration.
Abstract: With the completion of genomic sequencing of rice, rice has been firmly established as a model organism for both basic and applied research. The next challenge is to uncover the functions of genes predicted by sequence analysis. Considering the amount of effort and the diversity of disciplines required for functional analyses, extensive international collaboration is needed for this next goal. The aims of this review are to summarize the current status of rice mutant resources, key tools for functional analysis of genes, and our perspectives on how to accelerate rice gene discovery through collaboration.
250 citations
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TL;DR: The authors report crystal structures of a PET-hydrolyzing enzyme from the microbe Ideonella sakaiensis bound to substrate and product analogs, and suggest a catalytic mechanism for its PET-degrading activity.
Abstract: PET hydrolase (PETase), which hydrolyzes polyethylene terephthalate (PET) into soluble building blocks, provides an attractive avenue for the bioconversion of plastics. Here we present the structures of a novel PETase from the PET-consuming microbe Ideonella sakaiensis in complex with substrate and product analogs. Through structural analyses, mutagenesis, and activity measurements, a substrate-binding mode is proposed, and several features critical for catalysis are elucidated.
250 citations
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TL;DR: In this paper, the production cross sections of the inclusive Drell-Yan processes W-+/- -> l nu and Z/gamma* -> ll (l = e, mu) are measured in proton-proton collisions at root s = 7 TeV with the ATLAS detector.
Abstract: The production cross sections of the inclusive Drell-Yan processes W-+/- -> l nu and Z/gamma* -> ll (l = e, mu) are measured in proton-proton collisions at root s = 7 TeV with the ATLAS detector. The cross sections are reported integrated over a fiducial kinematic range, extrapolated to the full range, and also evaluated differentially as a function of the W decay lepton pseudorapidity and the Z boson rapidity, respectively. Based on an integrated luminosity of about 35 pb(-1) collected in 2010, the precision of these measurements reaches a few percent. The integrated and the differential W-+/- and Z/gamma* cross sections in the e and mu channels are combined, and compared with perturbative QCD calculations, based on a number of different parton distribution sets available at next-to-next-to-leading order.
250 citations
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TL;DR: In this article, the authors study the evolution of galaxy pair fractions and merger rates for different types of galaxies using kinematic pairs selected from the DEEP2 Redshift Survey, combined with other surveys at lower redshifts.
Abstract: We study the redshift evolution of galaxy pair fractions and merger rates for different types of galaxies using kinematic pairs selected from the DEEP2 Redshift Survey, combined with other surveys at lower redshifts. By parameterizing the evolution of the pair fraction as -->(1 + z)m, we find that the companion rate increases mildly with redshift with -->m = 0.41 ± 0.20 for all galaxies with – -->21 m = 1.27 ± 0.35, while the red companion rate of red galaxies is better fitted with the negative slope -->m = − 0.92 ± 0.59. For the chosen luminosity range, we find that at low redshift the pair fraction within the red sequence exceeds that of the blue cloud, indicating a higher merger probability among red galaxies compared to that among the blue galaxies. With further assumptions on the merger timescale and the fraction of pairs that will merge, the galaxy major merger rates for -->0.1 10−3 h3 Mpc −3 Gyr −1 with a factor of 2 uncertainty. At -->z ~ 1.1, 68% of mergers are wet, 8% of mergers are dry, and 24% of mergers are mixed, compared to 31% wet mergers, 25% dry mergers, and 44% mixed mergers at -->z ~ 0.1. Wet mergers dominate merging events at -->z = 0.2–1.2, but the relative importance of dry and mixed mergers increases over time. About 22%-54% of present-day -->L* galaxies have experienced major mergers since -->z ~ 1.2, depending on the definition of major mergers. Moreover, 24% of the red galaxies at the present epoch have had dry mergers with luminosity ratios between $1t{:}t 4$ --> and $4t{:}t 1$ --> since -->z ~ 1. Our results also suggest that the wet mergers and/or mixed mergers may be partially responsible for producing red galaxies with intermediate masses, while a significant portion of massive red galaxies are assembled through dry mergers at later times.
249 citations
Authors
Showing all 52129 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yi Chen | 217 | 4342 | 293080 |
Jing Wang | 184 | 4046 | 202769 |
Jie Zhang | 178 | 4857 | 221720 |
Hyun-Chul Kim | 176 | 4076 | 183227 |
Yang Yang | 164 | 2704 | 144071 |
Yuh Nung Jan | 162 | 460 | 74818 |
Jongmin Lee | 150 | 2257 | 134772 |
Hui-Ming Cheng | 147 | 880 | 111921 |
Teruki Kamon | 142 | 2034 | 115633 |
Jian Yang | 142 | 1818 | 111166 |
I. V. Gorelov | 139 | 1916 | 103133 |
S. R. Hou | 139 | 1845 | 106563 |
Kaori Maeshima | 139 | 1850 | 105218 |
Jiangyong Jia | 138 | 1173 | 91163 |
Kenneth Bloom | 138 | 1958 | 110129 |