Evidence map›Paper›PMID 39348061›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

Computational Analysis of T-Cell Receptor Repertoire Workflow: From T-Cell Isolation to Bioinformatics Analysis.

Roberta Amoriello, Olfa Maghrebi, Clara Ballerini

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 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

3 authors.

Roberta AmorielloDepartment of Experimental and Clinical Medicine, University of Florence, Florence, Italy. roberta.amoriello@unifi.it.
Olfa MaghrebiDepartment of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
Clara BalleriniDepartment of Experimental and Clinical Medicine, University of Florence, Florence, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The T-cell receptor (TCR) is the key molecule involved in the adaptive immune response. It is generated by the V(D)J recombination, responsible of the enormous diversity of the TCR repertoire, a crucial feature determining the individual capability to response to antigens and to build immunological memory. A pivotal role in the recognition of antigen is played by the hypervariable complementarity-determining region 3 (CDR3) of the V-beta chain of TCR. Investigating the CDR3 supports the understanding of the adaptive immune system dynamics in physiological processes, such as immune aging, and in disease, especially autoimmune disorders in which T cells are main actors. High-throughput sequencing (HTS) paved the way for a great progress in the investigation of TCR repertoire, enhancing the read depth in the process of library generation of sequencing and the number of samples that can be analyzed simultaneously. Therefore, the leverage of big datasets stressed the need to develop computational approach, by bioinformatics, to unravel the characteristics of the TCR repertoire.

Indexed as

Complementarity Determining RegionsComputational BiologyHigh-Throughput Nucleotide SequencingReceptors, Antigen, T-CellT-LymphocytesWorkflowCell SeparationHumansV(D)J RecombinationComplementarity Determining RegionsReceptors, Antigen, T-CellAgingBioinformaticsDiseaseHigh-throughput sequencingTCR repertoire

Identifiers

PMID39348061

What OpenQuestion holds

Textmetadata
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.