Evidence map›Paper›PMID 40060692›Full record

ArticlebioRxiv : the preprint server for biology2025

PepCentric Enables Fast Repository-Scale Proteogenomics Searches.

Fengchao Yu, Andy T Kong, Yi Hsiao, Alexey I Nesvizhskii

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 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

4 authors.

Fengchao YuDepartment of Pathology, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0002-7695-3698
Andy T KongDepartment of Pathology, University of Michigan, Ann Arbor, MI, USA.
Yi HsiaoDepartment of Pathology, University of Michigan, Ann Arbor, MI, USA.
Alexey I NesvizhskiiDepartment of Pathology, University of Michigan, Ann Arbor, MI, USA.

Funding

COMPUTATIONAL TOOLS FOR MASS SPECTROMETRY-BASED INTERACTOME DATAR01GM094231 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Alexey I Nesvizhskii · 2010 to 2026
$5.4M
Michigan Center for Translational Cancer Proteogenomics-Diversity SupplementU24CA271037 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Saravana Mohan Dhanasekaran, Alexey I Nesvizhskii · 2022 to 2026
$4.4M
University of Michigan Proteogenomics Data Analysis CenterU24CA210967 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CHINNAIYAN, ARUL M, DHANASEKARAN, SARAVANA M · 2016 to 2020
$4.1M
NCI NIH HHS U24 CA210967NCI NIH HHS U24 CA271037NIGMS NIH HHS R01 GM094231
6 · The paper itself

Abstract

Identifying novel peptides arising from alternative splicing, mutations, or non-canonical translations is a crucial yet challenging aspect of proteogenomics. We introduce PepCentric, a scalable computational platform and a web-based portal utilizing advanced 2-D fragment indexing for rapid peptide-centric searches across extensive mass spectrometry datasets. With robust false discovery rate control and optimized search performance, PepCentric offers an efficient tool for validating novel peptides and exploring proteomic variations. In a matter of seconds, users can search their novel peptides or proteins against 2.3 billion spectra collected from 66700 mass spectrometry runs, making it practical to rapidly validate proteogenomic hypotheses.

Identifiers

PMID40060692
PMCPMC11888313

What OpenQuestion holds

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LicenceCC BY-ND
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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 OpenQuestion graph.