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Institution

Sichuan University

EducationChengdu, China
About: Sichuan University is a education organization based out in Chengdu, China. It is known for research contribution in the topics: Population & Catalysis. The organization has 107623 authors who have published 102844 publications receiving 1612131 citations. The organization is also known as: Sìchuān Dàxué.


Papers
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Journal ArticleDOI
TL;DR: DTINet is introduced, whose performance is enhanced in the face of noisy, incomplete and high-dimensional biological data by learning low-dimensional vector representations, which accurately explains the topological properties of individual nodes in the heterogeneous network.
Abstract: The emergence of large-scale genomic, chemical and pharmacological data provides new opportunities for drug discovery and repositioning. In this work, we develop a computational pipeline, called DTINet, to predict novel drug-target interactions from a constructed heterogeneous network, which integrates diverse drug-related information. DTINet focuses on learning a low-dimensional vector representation of features, which accurately explains the topological properties of individual nodes in the heterogeneous network, and then makes prediction based on these representations via a vector space projection scheme. DTINet achieves substantial performance improvement over other state-of-the-art methods for drug-target interaction prediction. Moreover, we experimentally validate the novel interactions between three drugs and the cyclooxygenase proteins predicted by DTINet, and demonstrate the new potential applications of these identified cyclooxygenase inhibitors in preventing inflammatory diseases. These results indicate that DTINet can provide a practically useful tool for integrating heterogeneous information to predict new drug-target interactions and repurpose existing drugs.Network-based data integration for drug-target prediction is a promising avenue for drug repositioning, but performance is wanting. Here, the authors introduce DTINet, whose performance is enhanced in the face of noisy, incomplete and high-dimensional biological data by learning low-dimensional vector representations.

502 citations

Journal ArticleDOI
TL;DR: The chemistry, biology, and procedures for safe and efficient irrigation are summarized and cutting-edge information on the most recent developments are provided.

495 citations

Journal ArticleDOI
TL;DR: The design of a new family of C(2)-symmetric N,N'-dioxides from readily available chiral amino acids is outlined, and the application of these chiral amine N-oxides as useful metal ligands and organocatalysts for asymmetric reactions are discussed.
Abstract: Homochiral catalysts that can effect asymmetric transformations are invaluable in the production of optically active molecules. Researchers are actively pursuing the design of new ligands and organocatalysts by exploiting concepts derived from the application of bifunctional and C2-symmetric catalysts. Many homochiral catalysts containing amines, ethers, alcohols, and phosphines as electron-pair donors have been successfully developed.Amine N-oxides are highly polar substances. Despite their pronounced capacity as electron-pair donors, N-oxides have been underutilized in asymmetric reactions; they have only made a visible impact on the field in the preceding decade. Systematic studies have instead largely focused on pyridine- or quinoline-based scaffolds in organosilicon and coordination chemistry. The application of chiral tertiary amine N-oxides has not been widely pursued because of the difficulty of controlling the chirality at the tetrahedral nitrogen of the N-oxide moiety. In this Account, we outlin...

494 citations

Journal ArticleDOI
TL;DR: Investigation of human endometrial cancer in which a hotspot R298P mutation is present in a key component of the methyltransferase complex reveals reduced m6A mRNA methylation as an oncogenic mechanism in endometricrial cancer and identifies m 6A methylationAs a regulator of AKT signalling.
Abstract: N6-methyladenosine (m6A) messenger RNA methylation is a gene regulatory mechanism affecting cell differentiation and proliferation in development and cancer. To study the roles of m6A mRNA methylation in cell proliferation and tumorigenicity, we investigated human endometrial cancer in which a hotspot R298P mutation is present in a key component of the methyltransferase complex (METTL14). We found that about 70% of endometrial tumours exhibit reductions in m6A methylation that are probably due to either this METTL14 mutation or reduced expression of METTL3, another component of the methyltransferase complex. These changes lead to increased proliferation and tumorigenicity of endometrial cancer cells, likely through activation of the AKT pathway. Reductions in m6A methylation lead to decreased expression of the negative AKT regulator PHLPP2 and increased expression of the positive AKT regulator mTORC2. Together, these results reveal reduced m6A mRNA methylation as an oncogenic mechanism in endometrial cancer and identify m6A methylation as a regulator of AKT signalling.

492 citations

Journal ArticleDOI
TL;DR: In this paper, a combination of high pressure compression molding plus salt-leaching was first proposed to prepare porous graphene/polystyrene composites, and specific shielding effectiveness was as high as 64.4 dB cm3 g−1, the highest value ever reported for polymer based EMI shielding materials at such a low thickness (2.5 mm).
Abstract: A combination of high-pressure compression molding plus salt-leaching was first proposed to prepare porous graphene/polystyrene composites. The specific shielding effectiveness of the lightweight composite was as high as 64.4 dB cm3 g−1, the highest value ever reported for polymer based EMI shielding materials at such a low thickness (2.5 mm).

491 citations


Authors

Showing all 108474 results

NameH-indexPapersCitations
Jie Zhang1784857221720
Robin M. Murray1711539116362
Xiang Zhang1541733117576
Rui Zhang1512625107917
Xiaoyuan Chen14999489870
Yi Yang143245692268
Xinliang Feng13472173033
Chuan He13058466438
Lei Zhang130231286950
Jian Zhou128300791402
Shaobin Wang12687252463
Yi Xie12674562970
Pak C. Sham124866100601
Wei Chen122194689460
Bo Wang119290584863
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023339
20221,712
202113,846
202011,702
20199,714
20187,906