Evidence map›Paper›PMID 35415410›Full record

ArticleJournal of healthcare informatics research2018

On Comprehensive Mass Spectrometry Data Analysis for Proteome Profiling of Human Blood Samples.

Sameer Manchanda, Mikaela Meyer, Qianqian Li, Kai Liang, Yan Li, Nan Kong

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In one paragraph

Article in Journal of healthcare informatics research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

6 authors.

Sameer ManchandaDepartment of Computer Science, Purdue University, West Lafayette, USA.
Mikaela MeyerDepartment of Statistics and Mathematics, Purdue University, West Lafayette, IN USA.
Qianqian LiInstitute of Biophysics, Chinese Academy of Sciences, Beijing, China.
Kai LiangInstitute of Biophysics, Chinese Academy of Sciences, Beijing, China.
Yan LiInstitute of Biophysics, Chinese Academy of Sciences, Beijing, China.
Nan KongWeldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Dr, West Lafayette, IN 47906 USA.ORCID 0000-0002-4047-3414

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To guarantee meaningful interpretation of data in basic and translational medicine, it is critical to ensure the quality of biological samples. Mass spectrometers have become promising instruments to acquire proteomic information that is known to be associated with the quality of samples. However, a universally applicable mass spectrometry data analysis platform for quality assessment remains of great need. We present a comprehensive pattern recognition study to facilitate the development of such a platform. This study involves feature extraction, binary classification, and feature ranking. In this study, we develop classifiers with classification accuracy higher than 90% in distinguishing human serum samples stored for different amounts of time. We also derive fingerprint patterns of serum peptides that can be conveniently used for temporal classification.

Indexed as

Binary classificationBlood sampleFeature rankingMass spectrometryProteome profiling

Identifiers

PMID35415410
PMCPMC8982741

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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.