TY - JOUR
T1 - GNIFdb
T2 - A neoantigen intrinsic feature database for glioma
AU - Li, Wendong
AU - Sun, Ting
AU - Li, Muyang
AU - He, Yufei
AU - Li, Lin
AU - Wang, Lu
AU - Wang, Haoyu
AU - Li, Jing
AU - Wen, Hao
AU - Liu, Yong
AU - Chen, Yifan
AU - Fan, Yubo
AU - Xin, Beibei
AU - Zhang, Jing
N1 - Publisher Copyright:
© 2022 The Author(s). Published by Oxford University Press.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85124577874
U2 - 10.1093/database/baac004
DO - 10.1093/database/baac004
M3 - 文章
C2 - 35150127
AN - SCOPUS:85124577874
SN - 1758-0463
VL - 2022
JO - Database : the journal of biological databases and curation
JF - Database : the journal of biological databases and curation
M1 - baac004
ER -