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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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