Author

Yuyu Li

Shanghai Academy of Science & TechnologyORCID 0000-0002-3984-0889Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Organism:human· 2 Assay:proteomics· 2 Research Focus:differential expression· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1 Assay:whole-exome sequencing· 1

Frequent Co-Authors

Jian OuyangiD· 2 shared Lu XieiD· 2 shared Xiaoxiu Tan· 2 shared Guangzhi WangiD· 1 shared Guangzhi WangiD· 1 shared Huihui Wan· 1 shared Lanming CheniD· 1 shared Menghuan ZhangiD· 1 shared

Activity by Year

2020-2020 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 35 mutual co-author links

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2 shared papersBioinformatics

Jian OuyangORCID

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2 papers

Recent·Most cited

ProGeo-neo: a Customized Proteogenomic Workflow for Neoantigen Prediction and Selection

Yuyu Li, Guangzhi Wang, Xiaoxiu Tan, Jian Ouyang, Menghuan Zhang, Xiaofeng Song, Qi Liu, Qibin Leng, Lanming Chen, Lu Xie

ProGeo-neo integrates genomic and proteomic data to improve neoantigen prediction by incorporating mass spectrometry validation and MHC binding prediction.

BMC Medical Genomics · Apr 1, 2020Peer-reviewedBioinformatics

INeo-Epp: A novel T-cell HLA class-I immunogenicity or neoantigenic epitope prediction method based on sequence related amino acid features

Guangzhi Wang, Huihui Wan, Xingxing Jian, Yuyu Li, Jian Ouyang, Xiaoxiu Tan, Yong Zhao, Yong Lin, Lu Xie

The paper introduces INeo-Epp, a method for predicting T-cell HLA class-I immunogenic epitopes and neoantigens using sequence-related amino acid features, achieving AUC scores of 0.81 and 0.78.

BioMed Research International · Jan 1, 2020Peer-reviewedBioinformatics