Institution
King Abdullah University of Science and Technology
Education•Jeddah, Saudi Arabia•
About: King Abdullah University of Science and Technology is a education organization based out in Jeddah, Saudi Arabia. It is known for research contribution in the topics: Catalysis & Membrane. The organization has 6221 authors who have published 22019 publications receiving 625706 citations. The organization is also known as: KAUST.
Topics: Catalysis, Membrane, Computer science, Fading, Population
Papers published on a yearly basis
Papers
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31 Oct 2019TL;DR: This work proposes an efficient algorithm to embed a given image into the latent space of StyleGAN, which enables semantic image editing operations that can be applied to existing photographs.
Abstract: We propose an efficient algorithm to embed a given image into the latent space of StyleGAN. This embedding enables semantic image editing operations that can be applied to existing photographs. Taking the StyleGAN trained on the FFHD dataset as an example, we show results for image morphing, style transfer, and expression transfer. Studying the results of the embedding algorithm provides valuable insights into the structure of the StyleGAN latent space. We propose a set of experiments to test what class of images can be embedded, how they are embedded, what latent space is suitable for embedding, and if the embedding is semantically meaningful.
851 citations
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TL;DR: The roles of a range of genes involved in salt tolerance traits are reviewed, including ion exclusion, osmotic tolerance and tissue tolerance, which are a major constraint to agriculture.
850 citations
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TL;DR: This Review presents the main principles of operation and representative basic and clinical science applications of quantitative phase imaging, and aims to provide a critical and objective overview of this dynamic research field.
Abstract: Quantitative phase imaging (QPI) has emerged as a valuable method for investigating cells and tissues. QPI operates on unlabelled specimens and, as such, is complementary to established fluorescence microscopy, exhibiting lower phototoxicity and no photobleaching. As the images represent quantitative maps of optical path length delays introduced by the specimen, QPI provides an objective measure of morphology and dynamics, free of variability due to contrast agents. Owing to the tremendous progress witnessed especially in the past 10–15 years, a number of technologies have become sufficiently reliable and translated to biomedical laboratories. Commercialization efforts are under way and, as a result, the QPI field is now transitioning from a technology-development-driven to an application-focused field. In this Review, we aim to provide a critical and objective overview of this dynamic research field by presenting the scientific context, main principles of operation and current biomedical applications. Over the past 10–15 years, quantitative phase imaging has moved from a research-driven to an application-focused field. This Review presents the main principles of operation and representative basic and clinical science applications.
847 citations
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Centre for Life1, University of Toulouse2, National University of Singapore3, University of Bristol4, Massey University5, National Institute of Advanced Industrial Science and Technology6, National Institutes of Health7, Barcelona Biomedical Research Park8, King Abdullah University of Science and Technology9, Harry Perkins Institute of Medical Research10, Wayne State University11, University of Western Australia12, German Center for Neurodegenerative Diseases13, Charité14, University of Melbourne15, University of Queensland16, University of Tsukuba17, Karolinska Institutet18
TL;DR: This work integrates multiple transcript collections to generate a comprehensive atlas of 27,919 human lncRNA genes with high-confidence 5′ ends and expression profiles across 1,829 samples from the major human primary cell types and tissues, identifying 19,175 potentially functional lncRNAs in the human genome.
Abstract: Long non-coding RNAs (lncRNAs) are largely heterogeneous and functionally uncharacterized. Here, using FANTOM5 cap analysis of gene expression (CAGE) data, we integrate multiple transcript collections to generate a comprehensive atlas of 27,919 human lncRNA genes with high-confidence 5' ends and expression profiles across 1,829 samples from the major human primary cell types and tissues. Genomic and epigenomic classification of these lncRNAs reveals that most intergenic lncRNAs originate from enhancers rather than from promoters. Incorporating genetic and expression data, we show that lncRNAs overlapping trait-associated single nucleotide polymorphisms are specifically expressed in cell types relevant to the traits, implicating these lncRNAs in multiple diseases. We further demonstrate that lncRNAs overlapping expression quantitative trait loci (eQTL)-associated single nucleotide polymorphisms of messenger RNAs are co-expressed with the corresponding messenger RNAs, suggesting their potential roles in transcriptional regulation. Combining these findings with conservation data, we identify 19,175 potentially functional lncRNAs in the human genome.
821 citations
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TL;DR: This article aims at providing an integration of brain energy metabolism across resolution scales with decisive insights into the understanding of the cellular and molecular bases of the coupling between neuronal activity and energy metabolism.
806 citations
Authors
Showing all 6430 results
Name | H-index | Papers | Citations |
---|---|---|---|
Jian-Kang Zhu | 161 | 550 | 105551 |
Jean M. J. Fréchet | 154 | 726 | 90295 |
Kevin Murphy | 146 | 728 | 120475 |
Jean-Luc Brédas | 134 | 1026 | 85803 |
Carlos M. Duarte | 132 | 1173 | 86672 |
Kazunari Domen | 130 | 908 | 77964 |
Jian Zhou | 128 | 3007 | 91402 |
Tai-Shung Chung | 119 | 879 | 54067 |
Donal D. C. Bradley | 115 | 652 | 65837 |
Lain-Jong Li | 113 | 627 | 58035 |
Hong Wang | 110 | 1633 | 51811 |
Peng Wang | 108 | 1672 | 54529 |
Juan Bisquert | 107 | 450 | 46267 |
Jian Zhang | 107 | 3064 | 69715 |
Karl Leo | 104 | 832 | 42575 |