Evidence map›Paper›PMID 37287487›Full record

ArticleBiophysics reports2021

How to use open-pFind in deep proteomics data analysis?- A protocol for rigorous identification and quantitation of peptides and proteins from mass spectrometry data.

Guangcan Shao, Yong Cao, Zhenlin Chen, Chao Liu, Shangtong Li, Hao Chi, Meng-Qiu Dong

Abstract read
In one paragraph

Article in Biophysics reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

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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

23 citing papers in PubMed.

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  4. Proceedings of the National Academy of Sciences of the United States of America · 2025
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  9. A novel recognition of the major allergen, Hum j 1, fromThe World Allergy Organization journal · 2025
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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

7 authors.

Guangcan ShaoSchool of Life Sciences, Peking University, Beijing 100871, China.
Yong CaoSchool of Life Sciences, Peking University, Beijing 100871, China.
Zhenlin ChenKey Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), University of CAS, Institute of Computing Technology, CAS, Beijing 100190, China.
Chao LiuKey Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), University of CAS, Institute of Computing Technology, CAS, Beijing 100190, China.
Shangtong LiNational Institute of Biological Sciences, Beijing, Beijing 102206, China.
Hao ChiKey Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), University of CAS, Institute of Computing Technology, CAS, Beijing 100190, China.
Meng-Qiu DongNational Institute of Biological Sciences, Beijing, Beijing 102206, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-throughput proteomics based on mass spectrometry (MS) analysis has permeated biomedical science and propelled numerous research projects. pFind 3 is a database search engine for high-speed and in-depth proteomics data analysis. pFind 3 features a swift open search workflow that is adept at uncovering less obvious information such as unexpected modifications or mutations that would have gone unnoticed using a conventional data analysis pipeline. In this protocol, we provide step-by-step instructions to help users mastering various types of data analysis using pFind 3 in conjunction with pParse for data pre-processing and if needed, pQuant for quantitation. This streamlined pParse-pFind-pQuant workflow offers exceptional sensitivity, precision, and speed. It can be easily implemented in any laboratory in need of identifying peptides, proteins, or post-translational modifications, or of quantitation based on

Indexed as

Mass spectrometryOpen-pFindProtein identificationQuantitationSearch engine

Identifiers

PMID37287487
PMCPMC10244800

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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.