Evidence mapPaperPMID 41209766Full record

ArticleComputational and structural biotechnology journal2025

Immunolyser 2.0: An advanced computational pipeline for comprehensive analysis of immunopeptidomic data.

Prithvi Raj Munday, Sanjay S G Krishna, Joshua Fehring, Nathan P Croft, Anthony W Purcell, Chen Li, Asolina Braun

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2025. 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
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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.

Prithvi Raj MundayDepartment of Biochemistry and Molecular Biology and Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia.
Sanjay S G KrishnaDepartment of Biochemistry and Molecular Biology and Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia.
Joshua FehringDepartment of Biochemistry and Molecular Biology and Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia.
Nathan P CroftDepartment of Biochemistry and Molecular Biology and Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia.
Anthony W PurcellDepartment of Biochemistry and Molecular Biology and Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia.
Chen LiDepartment of Biochemistry and Molecular Biology and Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia.
Asolina BraunDepartment of Biochemistry and Molecular Biology and Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immunopeptidomics interrogates the peptide repertoire presented on the cell surface by major histocompatibility complex (MHC) molecules for T cell immune recognition. Advanced mass-spectrometry-based techniques have enabled rapid accumulation of immunopeptidomic data, posing a significant challenge for automated and efficient analysis of these large-scale datasets. To tackle this challenge, we introduced Immunolyser 1.0, a computational pipeline to streamline key analyses of immunopeptidomic data, including peptide length distribution, motif analysis, peptide clustering, and peptide-MHC binding prediction. Here, we present Immunolyser 2.0 with upgraded functionalities and an improved user interface. Major updates in Immunolyser 2.0 include (i) expanded functionality allowing analysis of murine immunopeptidomic datasets; (ii) a novel algorithm, MHC-TP, to predict the MHC class I haplotype

Indexed as

Antigen processing and presentationImmunopeptidomicsMajor Histocompatibility ComplexPeptide analysisProtein alignment

Identifiers

PMID41209766
PMCPMC12590289

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.