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GNIFdb: A neoantigen intrinsic feature database for glioma

  • Wendong Li
  • , Ting Sun
  • , Muyang Li
  • , Yufei He
  • , Lin Li
  • , Lu Wang
  • , Haoyu Wang
  • , Jing Li
  • , Hao Wen
  • , Yong Liu
  • , Yifan Chen
  • , Yubo Fan*
  • , Beibei Xin*
  • , Jing Zhang*
  • *此作品的通讯作者

科研成果: 期刊稿件文章同行评审

摘要

Neoantigens are mutation-containing immunogenic peptides from tumor cells. Neoantigen intrinsic features are neoantigens' sequence-associated features characterized by different amino acid descriptors and physical-chemical properties, which have a crucial function in prioritization of neoantigens with immunogenic potentials and predicting patients with better survival. Different intrinsic features might have functions to varying degrees in evaluating neoantigens' potentials of immunogenicity. Identification and comparison of intrinsic features among neoantigens are particularly important for developing neoantigen-based personalized immunotherapy. However, there is still no public repository to host the intrinsic features of neoantigens. Therefore, we developed GNIFdb, a glioma neoantigen intrinsic feature database specifically designed for hosting, exploring and visualizing neoantigen and intrinsic features. The database provides a comprehensive repository of computationally predicted Human leukocyte antigen class I (HLA-I) restricted neoantigens and their intrinsic features; a systematic annotation of neoantigens including sequence, neoantigen-associated mutation, gene expression, glioma prognosis, HLA-I subtype and binding affinity between neoantigens and HLA-I; and a genome browser to visualize them in an interactive manner.

源语言英语
文章编号baac004
期刊Database : the journal of biological databases and curation
2022
DOI
出版状态已出版 - 2022

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