Evidence map›Paper›PMID 41348603›Full record

ArticleBriefings in bioinformatics2025

Finding coexisting combinations of posttranslational modifications with HomMTM spectra.

Kunyi Li, Lusheng Wang

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 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

2 authors.

Kunyi LiDepartment of Computer Science, City University of Hong Kong, 83 Tat Chee Ave., Hong Kong, China.
Lusheng WangDepartment of Computer Science, City University of Hong Kong, 83 Tat Chee Ave., Hong Kong, China.

Funding

General Research FundHong Kong Special Administrative Region, P.R. China CityU 11218423Hong Kong Special Administrative Region, P.R. China CityU 11218821National Science Foundation of China 61972329
6 · The paper itself

Abstract

Posttranslational modifications (PTMs) are common biochemical processes that occur after protein synthesis, playing a pivotal role in regulating the activity, localization, stability, and interaction of proteins. Phosphorylation is one of the most crucial and widely studied PTMs, which is widely implicated in cell signal pathways and regulates many cellular processes. For peptide identification with PTMs, tools based on tandem mass spectrum have been developed. However, the existing tools report only one peptide isoform for a given query spectrum, ignoring the probability that multiple isoforms coexist in one single spectrum, which is important for analyzing how different combinations of modifications coexist and compete in cells, leading to diverse functional outcomes. In this paper, we present a workflow to find coexisting combinations of PTMs, aiming at exploring the possibility of simultaneously identifying multiple isoforms from the query spectrum. An algorithm is designed for the identification of at most two isoforms coexisting in a query spectrum. Applying our method to two real phosphopeptide datasets, U2OS and UCEC, we found that coexisting phosphopeptide isoforms occur in 2.16% of the U2OS dataset and 7.19% of the UCEE dataset. To further evaluate the performance of our algorithm for isoform identification, we develop a simulator for generating simulated spectrum with the corresponding ground-truth isoforms. Experiments on the simulated datasets show that our algorithm can achieve an isoform identification accuracy of 85.4%.

Indexed as

AlgorithmsPhosphopeptidesProtein Processing, Post-TranslationalDatabases, ProteinHumansPhosphorylationProtein IsoformsProteomicsTandem Mass SpectrometryPhosphopeptidesProtein Isoformscoexisting combinations of post-translational modificationspeak error correction alignmentphosphopeptide isoforms identification and quantification

Identifiers

PMID41348603
PMCPMC13223601

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.