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TEGR:A comprehensive Ericaceae genome resource database
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作者 Xiaojing Wang Yunfeng Wei +3 位作者 Zhuo Liu Tong Yu Yanhong Fu Xiaoming Song 《Journal of Integrative Agriculture》 2025年第3期1140-1151,共12页
Ericaceae is a diverse family of flowering plants distributed nearly worldwide,and it includes 126 genera and more than 4,000 species.In the present study,we developed The Ericaceae Genome Resource(TEGR,http://www.teg... Ericaceae is a diverse family of flowering plants distributed nearly worldwide,and it includes 126 genera and more than 4,000 species.In the present study,we developed The Ericaceae Genome Resource(TEGR,http://www.tegr.com.cn)as a comprehensive,user-friendly,web-based functional genomic database that is based on 16 published genomes from 16 Ericaceae species.The TEGR database contains information on many important functional genes,including 763 auxin genes,2,407 flowering genes,20,432 resistance genes,617 anthocyanin-related genes,and 470 N^(6)-methyladenosine(m^(6)A)modification genes.We identified a total of 599,174 specific guide sequences for CRISPR in the TEGR database.The gene duplication events,synteny analysis,and orthologous analysis of the16 Ericaceae species were performed using the TEGR database.The TEGR database contains 614,821 functional genes annotated through the GO,Nr,Pfam,TrEMBL,and Swiss-Prot databases.The TEGR database provides the Primer Design,Hmmsearch,Synteny,BLAST,and JBrowse tools for helping users perform comprehensive comparative genome analyses.All the high-quality reference genome sequences,genomic features,gene annotations,and bioinformatics results can be downloaded from the TEGR database.In the future,we will continue to improve the TEGR database with the latest data sets when they become available and to provide a useful resource that facilitates comparative genomic studies. 展开更多
关键词 TEGR ERICACEAE gene functional annotation m^(6)A CRISPR bioinformatic tools
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TripletGO: Integrating Transcript Expression Profiles with Protein Homology Inferences for Gene Function Prediction
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作者 Yi-Heng Zhu Chengxin Zhang +4 位作者 Yan Liu Gilbert S.Omenn Peter L.Freddolino Dong-Jun Yu Yang Zhang 《Genomics, Proteomics & Bioinformatics》 SCIE CAS CSCD 2022年第5期1013-1027,共15页
Gene Ontology(GO)has been widely used to annotate functions of genes and gene products.Here,we proposed a new method,Triplet GO,to deduce GO terms of protein-coding and noncoding genes,through the integration of four ... Gene Ontology(GO)has been widely used to annotate functions of genes and gene products.Here,we proposed a new method,Triplet GO,to deduce GO terms of protein-coding and noncoding genes,through the integration of four complementary pipelines built on transcript expression profile,genetic sequence alignment,protein sequence alignment,and naīve probability.Triplet GO was tested on a large set of 5754 genes from 8 species(human,mouse,Arabidopsis,rat,fly,budding yeast,fission yeast,and nematoda)and 2433 proteins with available expression data from the third Critical Assessment of Protein Function Annotation challenge(CAFA3).Experimental results show that Triplet GO achieves function annotation accuracy significantly beyond the current state-of-the-art approaches.Detailed analyses show that the major advantage of Triplet GO lies in the coupling of a new triplet network-based profiling method with the feature space mapping technique,which can accurately recognize function patterns from transcript expression profiles.Meanwhile,the combination of multiple complementary models,especially those from transcript expression and protein-level alignments,improves the coverage and accuracy of the final GO annotation results.The standalone package and an online server of Triplet GO are freely available at https://zhanggroup.org/Triplet GO/. 展开更多
关键词 gene function annotation gene Ontology Transcript expression profile Triplet network Protein-level alignment
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