Institution
Chinese Academy of Sciences
Government•Beijing, Beijing, China•
About: Chinese Academy of Sciences is a government organization based out in Beijing, Beijing, China. It is known for research contribution in the topics: Catalysis & Population. The organization has 421602 authors who have published 634849 publications receiving 14894293 citations. The organization is also known as: CAS.
Topics: Catalysis, Population, Laser, Adsorption, Graphene
Papers published on a yearly basis
Papers
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TL;DR: A new member of the family ofemiconducting transition metal dichalcogenides, rhenium disulphide (ReS2), where such variation is absent and bulk behaves as electronically and vibrationally decoupled monolayers stacked together.
Abstract: Monolayers of transition metal dichalcogenides have emerged as interesting two-dimensional materials. Here, the authors show that in a new member of this family of compounds, rhenium disulphide, the layers in the bulk are vibrationally and electronically decoupled, so that they behave almost as monolayers.
907 citations
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TL;DR: A more inclusive new approach for analyzing duplication history is introduced here, which reveals an ancient whole-genome duplication, a recent segmental duplication on Chromosomes 11 and 12, and massive ongoing individual gene duplications.
Abstract: We report improved whole-genome shotgun sequences for the genomes of indica and japonica rice, both with multimegabase contiguity, or almost 1,000-fold improvement over the drafts of 2002. Tested against a nonredundant collection of 19,079 full-length cDNAs, 97.7% of the genes are aligned, without fragmentation, to the mapped super-scaffolds of one or the other genome. We introduce a gene identification procedure for plants that does not rely on similarity to known genes to remove erroneous predictions resulting from transposable elements. Using the available EST data to adjust for residual errors in the predictions, the estimated gene count is at least 38,000–40,000. Only 2%–3% of the genes are unique to any one subspecies, comparable to the amount of sequence that might still be missing. Despite this lack of variation in gene content, there is enormous variation in the intergenic regions. At least a quarter of the two sequences could not be aligned, and where they could be aligned, single nucleotide polymorphism (SNP) rates varied from as little as 3.0 SNP/kb in the coding regions to 27.6 SNP/kb in the transposable elements. A more inclusive new approach for analyzing duplication history is introduced here. It reveals an ancient whole-genome duplication, a recent segmental duplication on Chromosomes 11 and 12, and massive ongoing individual gene duplications. We find 18 distinct pairs of duplicated segments that cover 65.7% of the genome; 17 of these pairs date back to a common time before the divergence of the grasses. More important, ongoing individual gene duplications provide a never-ending source of raw material for gene genesis and are major contributors to the differences between members of the grass family.
907 citations
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TL;DR: Comprehensive results show that the proposed CE-Net method outperforms the original U- net method and other state-of-the-art methods for optic disc segmentation, vessel detection, lung segmentation , cell contour segmentation and retinal optical coherence tomography layer segmentation.
Abstract: Medical image segmentation is an important step in medical image analysis. With the rapid development of a convolutional neural network in image processing, deep learning has been used for medical image segmentation, such as optic disc segmentation, blood vessel detection, lung segmentation, cell segmentation, and so on. Previously, U-net based approaches have been proposed. However, the consecutive pooling and strided convolutional operations led to the loss of some spatial information. In this paper, we propose a context encoder network (CE-Net) to capture more high-level information and preserve spatial information for 2D medical image segmentation. CE-Net mainly contains three major components: a feature encoder module, a context extractor, and a feature decoder module. We use the pretrained ResNet block as the fixed feature extractor. The context extractor module is formed by a newly proposed dense atrous convolution block and a residual multi-kernel pooling block. We applied the proposed CE-Net to different 2D medical image segmentation tasks. Comprehensive results show that the proposed method outperforms the original U-Net method and other state-of-the-art methods for optic disc segmentation, vessel detection, lung segmentation, cell contour segmentation, and retinal optical coherence tomography layer segmentation.
906 citations
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TL;DR: The CADA reactions discussed herein include oxidative dearomatization reactions, dearomAtization by Diels-Alder and related reactions, the alkylative dearom atization of electron-rich arenes, transition-metal-catalyzed dearomatography reactions, cascade sequences involving asymmetric dearmatization as the key step, and nucleophilic dearomATization reactions of pyridinium derivatives.
Abstract: This Review summarizes the development of catalytic asymmetric dearomatization (CADA) reactions. The CADA reactions discussed herein include oxidative dearomatization reactions, dearomatization by DielsAlder and related reactions, the alkylative dearomatization of electron-rich arenes, transition-metal-catalyzed dearomatization reactions, cascade sequences involving asymmetric dearomatization as the key step, and nucleophilic dearomatization reactions of pyridinium derivatives. Asymmetric dearomatization reactions with chiral auxiliaries and catalytic asymmetric reactions of dearomatized substrates are also briefly introduced. This Review intends to provide a concept for catalytic asymmetric dearomatization.
905 citations
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TL;DR: Long noncoding RNAs (lncRNAs) are emerging as important regulators in gene expression networks by controlling nuclear architecture and transcription in the nucleus and by modulating mRNA stability, translation and post-translational modifications in the cytoplasm as mentioned in this paper.
Abstract: A diverse catalog of long noncoding RNAs (lncRNAs), which lack protein-coding potential, are transcribed from the mammalian genome. They are emerging as important regulators in gene expression networks by controlling nuclear architecture and transcription in the nucleus and by modulating mRNA stability, translation and post-translational modifications in the cytoplasm. In this Review, we highlight recent progress in cellular functions of lncRNAs at the molecular level in mammalian cells.
904 citations
Authors
Showing all 422053 results
Name | H-index | Papers | Citations |
---|---|---|---|
Frank B. Hu | 250 | 1675 | 253464 |
Zhong Lin Wang | 245 | 2529 | 259003 |
Yi Chen | 217 | 4342 | 293080 |
Jing Wang | 184 | 4046 | 202769 |
Peidong Yang | 183 | 562 | 144351 |
Xiaohui Fan | 183 | 878 | 168522 |
H. S. Chen | 179 | 2401 | 178529 |
Douglas Scott | 178 | 1111 | 185229 |
Jie Zhang | 178 | 4857 | 221720 |
Pulickel M. Ajayan | 176 | 1223 | 136241 |
Feng Zhang | 172 | 1278 | 181865 |
Andrea Bocci | 172 | 2402 | 176461 |
Yang Yang | 171 | 2644 | 153049 |
Lei Jiang | 170 | 2244 | 135205 |
Yang Gao | 168 | 2047 | 146301 |