RESUMO
Single-cell studies have delineated cellular diversity and uncovered increasing numbers of previously uncharacterized cell types in complex tissues. Thus, synthesizing growing knowledge of cellular characteristics is critical for dissecting cellular heterogeneity, developmental processes and tumorigenesis at single-cell resolution. Here, we present Cell Taxonomy (https://ngdc.cncb.ac.cn/celltaxonomy), a comprehensive and curated repository of cell types and associated cell markers encompassing a wide range of species, tissues and conditions. Combined with literature curation and data integration, the current version of Cell Taxonomy establishes a well-structured taxonomy for 3,143 cell types and houses a comprehensive collection of 26,613 associated cell markers in 257 conditions and 387 tissues across 34 species. Based on 4,299 publications and single-cell transcriptomic profiles of â¼3.5 million cells, Cell Taxonomy features multifaceted characterization for cell types and cell markers, involving quality assessment of cell markers and cell clusters, cross-species comparison, cell composition of tissues and cellular similarity based on markers. Taken together, Cell Taxonomy represents a fundamentally useful reference to systematically and accurately characterize cell types and thus lays an important foundation for deeply understanding and exploring cellular biology in diverse species.
RESUMO
LncRNAWiki, a knowledgebase of human long non-coding RNAs (lncRNAs), has been rapidly expanded by incorporating more experimentally validated lncRNAs. Since it was built based on MediaWiki as its database system, it fails to manage data in a structured way and is ineffective to support systematic exploration of lncRNAs. Here we present LncRNAWiki 2.0 (https://ngdc.cncb.ac.cn/lncrnawiki), which is significantly improved with enhanced database system and curation model. In LncRNAWiki 2.0, all contents are organized in a structured manner powered by MySQL/Java and curators are able to submit/edit annotations based on the curation model that includes a wider range of annotation items. Moreover, it is equipped with popular online tools to help users identify lncRNAs with potentially important functions, and provides more user-friendly web interfaces to facilitate data curation, retrieval and visualization. Consequently, LncRNAWiki 2.0 incorporates a total of 2512 lncRNAs and 106 242 associations for disease, function, drug, interacting partner, molecular signature, experimental sample, CRISPR design, etc., thus providing a comprehensive and up-to-date resource of functionally annotated lncRNAs in human.
Assuntos
Bases de Dados Genéticas , Bases de Conhecimento , RNA Longo não Codificante/genética , Software , Humanos , Internet , Anotação de Sequência Molecular , RNA Longo não Codificante/classificaçãoRESUMO
The design of Pt-based nanoarchitectures with controllable compositions and morphologies is necessary to enhance their electrocatalytic activity. Herein, we report a rational design and synthesis of anisotropic mesoporous Pt@Pt-skin Pt3Ni core-shell framework nanowires for high-efficient electrocatalysis. The catalyst has a uniform core-shell structure with an ultrathin atomic-jagged Pt nanowire core and a mesoporous Pt-skin Pt3Ni framework shell, possessing high electrocatalytic activity, stability and Pt utilisation efficiency. For the oxygen reduction reaction, the anisotropic mesoporous Pt@Pt-skin Pt3Ni core-shell framework nanowires demonstrated exceptional mass and specific activities of 6.69 A/mgpt and 8.42 mA/cm2 (at 0.9 V versus reversible hydrogen electrode), and the catalyst exhibited high stability with negligible activity decay after 50,000 cycles. The mesoporous Pt@Pt-skin Pt3Ni core-shell framework nanowire configuration combines the advantages of three-dimensional open mesopore molecular accessibility and compressive Pt-skin surface strains, which results in more catalytically active sites and weakened chemisorption of oxygenated species, thus boosting its catalytic activity and stability towards electrocatalysis.