Back

bacNeo: a computational toolkit for bacteria-derived neoantigen identification

Wang, Y.; Li, Y.; Gu, K. W.; Cheng, X.; Wen, B.; Zhang, Z.

2025-07-27 bioinformatics
10.1101/2025.07.23.666275 bioRxiv
Show abstract

Intratumour microbiome can restore anti-tumour immunity with bacterial peptides potentially serving as neoantigens, while robust in-silico tools for bacterial neoantigen identification remain lacking. We developed bacterial neoantigen (bacNeo), a multi-omics based computational toolkit that contains three modules to classify bacterial taxonomy, identify host HLA alleles, and predict bacterial neoantigens. bacNeo could enable personalised neoantigen discovery to advance therapeutic strategies across diverse cancer types.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Briefings in Bioinformatics
◐ 354 papers in training set
Top 0.4%
12.6%
Similar papers in this journal
2
Nature Communications
○ 5641 papers in training set
Top 16%
11.6%
Similar papers in this journal
3
Bioinformatics
◐ 1204 papers in training set
Top 3%
9.4%
Similar papers in this journal
4
Journal of Proteome Research
● 234 papers in training set
Top 0.5%
7.7%
Similar papers in this journal
5
Genome Biology
○ 637 papers in training set
Top 2%
5.3%
Similar papers in this journal
6
Communications Biology
○ 993 papers in training set
Top 3%
4.2%
50% of probability mass above
7
Nature Biotechnology
○ 172 papers in training set
Top 1%
3.9%
8
Bioinformatics Advances
◐ 203 papers in training set
Top 2%
3.9%
9
Scientific Reports
○ 3612 papers in training set
Top 29%
3.3%
10
BMC Bioinformatics
○ 457 papers in training set
Top 3%
3.0%
11
NAR Genomics and Bioinformatics
◐ 242 papers in training set
Top 2%
2.6%
12
GigaScience
◐ 212 papers in training set
Top 2%
2.3%
13
Nucleic Acids Research
◐ 1281 papers in training set
Top 8%
1.9%
14
Nature Methods
○ 385 papers in training set
Top 4%
1.9%
15
Computational and Structural Biotechnology Journal
● 242 papers in training set
Top 3%
1.9%
16
Nature Protocols
○ 33 papers in training set
Top 0.3%
1.7%
17
Patterns
○ 78 papers in training set
Top 1%
1.6%
18
Nature Machine Intelligence
○ 70 papers in training set
Top 2%
1.5%
19
iMeta
○ 10 papers in training set
Top 0.1%
1.5%
20
F1000Research
○ 88 papers in training set
Top 3%
1.1%
21
Analytical Chemistry
● 218 papers in training set
Top 2%
1.1%
22
Cell Reports Methods
○ 165 papers in training set
Top 3%
1.1%
23
mSystems
● 394 papers in training set
Top 6%
1.0%
24
iScience
○ 1154 papers in training set
Top 33%
1.0%
25
BMC Genomics
○ 406 papers in training set
Top 8%
0.8%
26
PLOS Computational Biology
● 1863 papers in training set
Top 20%
0.8%
27
Genomics, Proteomics & Bioinformatics
188 papers in training set
Top 2%
0.8%
28
Molecular Systems Biology
○ 162 papers in training set
Top 4%
0.6%
29
Nature Computational Science
○ 55 papers in training set
Top 2%
0.6%
30
PROTEOMICS
○ 43 papers in training set
Top 0.9%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.