Evidence map›Paper›PMID 36106020›Full record

ArticleFrontiers in molecular biosciences2022

RNA-sequencing and mass-spectrometry proteomic time-series analysis of T-cell differentiation identified multiple splice variants models that predicted validated protein biomarkers in inflammatory diseases.

Rasmus Magnusson, Olof Rundquist, Min Jung Kim, Sandra Hellberg, Chan Hyun Na, Mikael Benson, David Gomez-Cabrero, Ingrid Kockum, Jesper N Tegnér, Fredrik Piehl and 8 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in molecular biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 36% of its field
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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

18 authors at 7 institutions in 5 countries.

Rasmus MagnussonBioinformatics, Department of Physics, Chemistry and Biology, Linköping University, Linköping, Sweden.
Olof RundquistBioinformatics, Department of Physics, Chemistry and Biology, Linköping University, Linköping, Sweden.
Min Jung KimDepartment of Applied Chemistry, College of Applied Sciences, Kyung Hee University, Yong-in, South Korea.
Sandra HellbergDepartment of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden.
Chan Hyun NaDepartment of Neurology, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Mikael BensonCentre for Personalised Medicine, Linköping University, Linköping, Sweden.
David Gomez-CabreroNavarrabiomed, Complejo Hospitalario de Navarra, Universidad Pública de Navarra, IdiSNA, Pamplona, Spain.
Ingrid KockumDepartment of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden.
Jesper N TegnérBiological and Environmental Sciences and Engineering Division, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.
Fredrik PiehlDepartment of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden.
Maja JagodicDepartment of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden.
Johan MellergårdDepartment of Neurology, Linköping University, Linköping, Sweden.
Claudio AltafiniDepartment of Automatic Control, Linköping University, Linköping, Sweden.
Jan ErnerudhDepartment of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden.
Maria C JenmalmDepartment of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden.
Colm E NestorDepartment of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden.
Min-Sik KimDepartment of New Biology, Daegu Gyeongbuk Institute of Science and Technology, Daegu, South Korea.
Mika GustafssonBioinformatics, Department of Physics, Chemistry and Biology, Linköping University, Linköping, Sweden.
Linköping University · SEKarolinska Institutet · SEDaegu Gyeongbuk Institute of Science and Technology · KRJohns Hopkins Medicine · USKing Abdullah University of Science and Technology · SAKyung Hee University · KRNavarrabiomed · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Profiling of mRNA expression is an important method to identify biomarkers but complicated by limited correlations between mRNA expression and protein abundance. We hypothesised that these correlations could be improved by mathematical models based on measuring splice variants and time delay in protein translation. We characterised time-series of primary human naïve CD4

Indexed as

biomarkersmultiple sclerosisproteomicsRNA-seqT-cell differentiation

Identifiers

PMID36106020
PMCPMC9465313
OpenAlexW4293427391

What OpenQuestion 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 OpenQuestion graph.