Author

Ting Fang

BGI Group (China)ORCID 0000-0001-6233-9454Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Approach:deep learning· 1 Organism:human· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1 Assay:whole-exome sequencing· 1

Frequent Co-Authors

Cuicui Qiang· 2 shared Quanlei Zeng· 2 shared Shuixia Liu· 2 shared Yi ZhangiD· 2 shared Yun XiongiD· 2 shared Yuying YuaniD· 2 shared Chaoqun Pang· 1 shared Dao‐Ling HuangiD· 1 shared

Activity by Year

2021-2021 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 42 mutual co-author links

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2 shared papersBioinformatics

Cuicui Qiang

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintSep 15, 2021

Accurate Name Entity Recognition for Biomedical Literatures: A Combined High-quality Manual Annotation and Deep-learning Natural Language Processing Study

Dao‐Ling Huang, Quanlei Zeng, Yun Xiong…·Yuying Yuan

This study combines manual annotation and deep learning to improve name entity recognition in biomedical texts, achieving high F1-scores for gene, variant, disease, and species entities.

1 citation

deep learningbenchmarking

𝕏 PostBluesky

GeneticsHuman MutationPeer-reviewedFeb 10, 2021

Cancer SIGVAR: A semi-automated interpretation tool for germline variants of hereditary cancer-related genes

Hong Li, Shuixia Liu, Shuangying Wang…·Yun Xiong

Cancer SIGVAR is a tool for interpreting germline cancer variants using 21 and 48 criteria, achieving high consistency in classification across benchmark databases.

14 citations

humanwhole-exome sequencing

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