Evidence map›Paper›PMID 41288337›Full record

ArticleAnalytical chemistry2025

Resolution-Adaptive Binning Enhances Machine Learning Modeling by Interbatch and Multiplatform Orbitrap-Based Shotgun Mass Spectrometry Data Integration.

Hiu-Lok Ngan, Jialing Zhang, Kenneth Kin-Leung Kwan, Jacinth Wing-Sum Cheu, Li Zhong, Yike Guo, Xian Yang, Carmen Chak-Lui Wong, Hong Yan, Zongwei Cai

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Analytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Hiu-Lok NganState Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong 999077, P. R. China.ORCID 0000-0002-6002-9660
Jialing ZhangState Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong 999077, P. R. China.
Kenneth Kin-Leung KwanState Key Laboratory of Liver Research, Department of Pathology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong 999077, P. R. China.
Jacinth Wing-Sum CheuState Key Laboratory of Liver Research, Department of Pathology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong 999077, P. R. China.
Li ZhongState Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong 999077, P. R. China.
Yike GuoDepartment of Computer Science, Hong Kong Baptist University, Hong Kong 999077, P. R. China.
Xian YangDepartment of Computer Science, Hong Kong Baptist University, Hong Kong 999077, P. R. China.
Carmen Chak-Lui WongState Key Laboratory of Liver Research, Department of Pathology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong 999077, P. R. China.
Hong YanState Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong 999077, P. R. China.
Zongwei CaiState Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong 999077, P. R. China.ORCID 0000-0002-8724-7684

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Machine learning (ML) modeling on mass spectrometry (MS)-based shotgun data facilitates feature selection and disease modeling. However, batch-specific models often struggle with limited transferability and generalizability, necessitating data integration from multiple batches and platforms. Traditional binning methods can either disintegrate or aggregate

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsMachine LearningMass SpectrometryAnimalsHumansMice

Identifiers

PMID41288337
PMCPMC12874219

What OpenQuestion holds

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Registered trials

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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.