Back

Reference-guided immune recovery matching prioritizes traditional Chinese medicine ingredients

Hu, C.; Xiao, B.; Chen, C. Y.-C.

2026-06-22 bioinformatics
10.64898/2026.06.16.732528 bioRxiv
Show abstract

Therapeutic prioritization from single-cell transcriptomes requires a target that is closer to treatment response than disease-signature reversal. In immune diseases, post-treatment recovery may follow patient- and cell-type-specific trajectories rather than a simple return along the pretreatment disease axis. We developed ImmuneNavi, a healthy-reference-anchored recovery-matching workflow for ranking traditional Chinese medicine ingredients from paired PBMC data. The workflow maps heterogeneous PBMC cohorts to a common healthy immune coordinate system, constructs patient-cell-type disease and recovery states, and processes ITCM treated-control profiles into a fixed ingredient perturbation bank. Patient and ingredient states are represented in matched gene, pathway and transcription-factor views, allowing the model to combine local transcriptional direction with more stable program-level features. A matcher trained on one paired treatment cohort preserved recovery-aligned ingredient rankings in independent PBMC cohorts without redefining the feature space, candidate set or preprocessing procedure. This provides a reusable transcriptomic pipeline for moving from paired immune-state measurements to prioritized natural-product candidates for experimental follow-up.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Cell Systems
201 papers in training set
Top 0.2%
11.6%
2
Briefings in Bioinformatics
354 papers in training set
Top 0.7%
9.5%
3
Nature Communications
5641 papers in training set
Top 22%
7.7%
4
Nucleic Acids Research
1281 papers in training set
Top 2%
7.7%
5
Genome Biology
637 papers in training set
Top 2%
6.1%
6
Advanced Science
286 papers in training set
Top 1%
5.4%
7
PLOS Computational Biology
1863 papers in training set
Top 8%
4.7%
50% of probability mass above
8
Molecular Systems Biology
162 papers in training set
Top 0.5%
3.9%
9
Computational and Structural Biotechnology Journal
242 papers in training set
Top 1%
3.9%
10
Patterns
78 papers in training set
Top 0.9%
2.3%
11
npj Systems Biology and Applications
125 papers in training set
Top 0.8%
2.3%
12
NAR Genomics and Bioinformatics
242 papers in training set
Top 2%
2.1%
13
eLife
5828 papers in training set
Top 45%
2.1%
14
Genome Medicine
183 papers in training set
Top 2%
1.9%
15
Bioinformatics
1204 papers in training set
Top 7%
1.7%
16
Nature Machine Intelligence
70 papers in training set
Top 2%
1.7%
17
Cell Reports Methods
165 papers in training set
Top 2%
1.6%
18
iScience
1154 papers in training set
Top 21%
1.5%
19
Science Advances
1243 papers in training set
Top 26%
1.1%
20
Scientific Reports
3612 papers in training set
Top 67%
1.1%
21
Cell Genomics
172 papers in training set
Top 3%
1.1%
22
Proceedings of the National Academy of Sciences
2444 papers in training set
Top 36%
1.1%
23
Cell Reports Medicine
153 papers in training set
Top 4%
1.0%
24
BMC Bioinformatics
457 papers in training set
Top 5%
1.0%
25
Cell Reports
1498 papers in training set
Top 26%
1.0%
26
PLOS ONE
5266 papers in training set
Top 63%
0.8%
27
Communications Chemistry
48 papers in training set
Top 2%
0.8%
28
GigaScience
212 papers in training set
Top 5%
0.6%
29
Nature Biotechnology
172 papers in training set
Top 5%
0.6%