Evidence map›Paper›PMID 41307179›Full record

ArticleEmerging microbes & infections2025

Genome analysis and machine learning-based feature selection strategy reveal potential drug-resistance determinants in

Qiqi Wang, Runhong Chen, Xin Cao, Hao Zhang, Jielin Yang, Xinlong Wang, Yadong Liu, Xinyu Tan, Tianyu Liang, Ruoyu Li and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Emerging microbes & infections, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Qiqi WangDepartment of Dermatology and Venerology, Peking University First Hospital, National Clinical Research Center for Skin and Immune Diseases, Research Center for Medical Mycology, Peking University, Beijing Key Laboratory of Molecular Diagnosis on Dermatoses, Beijing, People's Republic of China.
Runhong ChenYouth Innovation Team of Medical Bioinformatics, Shenzhen University Health Science Center, Shenzhen, People's Republic of China.
Xin CaoYouth Innovation Team of Medical Bioinformatics, Shenzhen University Health Science Center, Shenzhen, People's Republic of China.
Hao ZhangDepartment of Dermatology, Jiangxi Provincial Children's Hospital, The Affiliated Children's Hospital of Nanchang Medical College, Nanchang, People's Republic of China.
Jielin YangYouth Innovation Team of Medical Bioinformatics, Shenzhen University Health Science Center, Shenzhen, People's Republic of China.
Xinlong WangYouth Innovation Team of Medical Bioinformatics, Shenzhen University Health Science Center, Shenzhen, People's Republic of China.
Yadong LiuState Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, People's Republic of China.
Xinyu TanState Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, People's Republic of China.
Tianyu LiangDepartment of Dermatology and Venerology, Peking University First Hospital, National Clinical Research Center for Skin and Immune Diseases, Research Center for Medical Mycology, Peking University, Beijing Key Laboratory of Molecular Diagnosis on Dermatoses, Beijing, People's Republic of China.
Ruoyu LiDepartment of Dermatology and Venerology, Peking University First Hospital, National Clinical Research Center for Skin and Immune Diseases, Research Center for Medical Mycology, Peking University, Beijing Key Laboratory of Molecular Diagnosis on Dermatoses, Beijing, People's Republic of China.
Zhe WanDepartment of Dermatology and Venerology, Peking University First Hospital, National Clinical Research Center for Skin and Immune Diseases, Research Center for Medical Mycology, Peking University, Beijing Key Laboratory of Molecular Diagnosis on Dermatoses, Beijing, People's Republic of China.
Yejun WangYouth Innovation Team of Medical Bioinformatics, Shenzhen University Health Science Center, Shenzhen, People's Republic of China.
Wei LiuDepartment of Dermatology and Venerology, Peking University First Hospital, National Clinical Research Center for Skin and Immune Diseases, Research Center for Medical Mycology, Peking University, Beijing Key Laboratory of Molecular Diagnosis on Dermatoses, Beijing, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Invasive candidiasis caused by

Indexed as

Antifungal AgentsDrug Resistance, FungalGenome, FungalMachine LearningCandidiasisChinaFungal ProteinsGenome-Wide Association StudyHumansMicrobial Sensitivity TestsMutationTriazolesWhole Genome SequencingAntifungal AgentsFungal ProteinsTriazolesantifungal resistancegenome analysisgenomic signaturesmachine learningNakaseomyces glabratusresistance determinants

Identifiers

PMID41307179
PMCPMC12704144

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.