Evidence map›Paper›PMID 38097182›Full record

ArticleMolecular & cellular proteomics : MCP2024

iProPhos: A Web-Based Interactive Platform for Integrated Proteome and Phosphoproteome Analysis.

Jing Zou, Ziran Qin, Ran Li, Xiaohua Yan, Huizhe Huang, Bing Yang, Fangfang Zhou, Long Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Jing ZouThe Second Affiliated Hospital and Life Sciences Institute and School of Medicine, The MOE Key Laboratory of Biosystems Homeostasis and Protection and Zhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Zhejiang University, Hangzhou, China.
Ziran QinThe Second Affiliated Hospital and Life Sciences Institute and School of Medicine, The MOE Key Laboratory of Biosystems Homeostasis and Protection and Zhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Zhejiang University, Hangzhou, China.
Ran LiSchool of Medicine, Hangzhou City University, Hangzhou, China. Electronic address: ranli1993@zju.edu.cn.
Xiaohua YanDepartment of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Nanchang University, Nanchang, China.
Huizhe HuangThe Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Bing YangThe Second Affiliated Hospital and Life Sciences Institute and School of Medicine, The MOE Key Laboratory of Biosystems Homeostasis and Protection and Zhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Zhejiang University, Hangzhou, China; Department of Pharmaceutical Chemistry and the Cardiovascular Research Institute, University of California, San Francisco, California, USA.
Fangfang ZhouInstitutes of Biology and Medical Sciences, Soochow University, Suzhou, China. Electronic address: zhoufangfang@suda.edu.cn.
Long ZhangThe Second Affiliated Hospital and Life Sciences Institute and School of Medicine, The MOE Key Laboratory of Biosystems Homeostasis and Protection and Zhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Zhejiang University, Hangzhou, China; Cancer Center, Zhejiang University, Hangzhou, China. Electronic address: L_Zhang@zju.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Large-scale omics studies have generated a wealth of mass spectrometry-based proteomics data, which provide additional insights into disease biology spanning genomic boundaries. However, there is a notable lack of web-based analysis and visualization tools that facilitate the reutilization of these data. Given this challenge, we present iProPhos, a user-friendly web server to deliver interactive and customizable functionalities. iProPhos incorporates a large number of samples, including 1444 tumor samples and 746 normal samples across 12 cancer types, sourced from the Clinical Proteomic Tumor Analysis Consortium. Additionally, users can also upload their own proteomics/phosphoproteomics data for analysis and visualization. In iProPhos, users can perform profiling plotting and differential expression, patient survival, clinical feature-related, and correlation analyses, including protein-protein, mRNA-protein, and kinase-substrate correlations. Furthermore, functional enrichment, protein-protein interaction network, and kinase-substrate enrichment analyses are accessible. iProPhos displays the analytical results in interactive figures and tables with various selectable parameters. It is freely accessible at http://longlab-zju.cn/iProPhos without login requirement. We present two case studies to demonstrate that iProPhos can identify potential drug targets and upstream kinases contributing to site-specific phosphorylation. Ultimately, iProPhos allows end-users to leverage the value of big data in cancer proteomics more effectively and accelerates the discovery of novel therapeutic targets.

Indexed as

NeoplasmsProteomeHumansInternetProteomicsSoftwareProteomeintegrated analysisphosphoproteomicsproteomicstumorweb server

Identifiers

PMID38097182
PMCPMC10828474

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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.