Evidence map›Paper›PMID 37707621›Full record

ArticleBulletin of mathematical biology2023

Mathematical Characterization of Private and Public Immune Receptor Sequences.

Lucas Böttcher, Sascha Wald, Tom Chou

Abstract read
In one paragraph

Article in Bulletin of mathematical biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. SURROGATE SELECTION OVERSAMPLES EXPANDED T CELL CLONOTYPES.The annals of applied statistics · 2025
    Article
  3. Article
  4. Review
  5. 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

3 authors.

Lucas BöttcherDepartment of Computational Science and Philosophy, Frankfurt School of Finance and Management, 60322, Frankfurt am Main, Germany. l.boettcher@fs.de.ORCID 0000-0003-1700-1897
Sascha WaldStatistical Physics Group, Centre for Fluid and Complex Systems, Coventry University, Priory Street, Coventry, CV1 5FB, UK.ORCID 0000-0003-1013-2130
Tom ChouDepartment of Computational Medicine, University of California, Los Angeles, 621 Charles E. Young Dr. S., Los Angeles, 90095-1766, CA, USA.ORCID 0000-0003-0785-6349

Funding

Tracking clonal dynamics during hematopoiesis: mechanistic insight via modeling and data analysisR01HL146552 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI CHOU, TOM · 2019 to 2022
$907k
NHLBI NIH HHS R01 HL146552
6 · The paper itself

Abstract

Diverse T and B cell repertoires play an important role in mounting effective immune responses against a wide range of pathogens and malignant cells. The number of unique T and B cell clones is characterized by T and B cell receptors (TCRs and BCRs), respectively. Although receptor sequences are generated probabilistically by recombination processes, clinical studies found a high degree of sharing of TCRs and BCRs among different individuals. In this work, we use a general probabilistic model for T/B cell receptor clone abundances to define "publicness" or "privateness" and information-theoretic measures for comparing the frequency of sampled sequences observed across different individuals. We derive mathematical formulae to quantify the mean and the variances of clone richness and overlap. Our results can be used to evaluate the effect of different sampling protocols on abundances of clones within an individual as well as the commonality of clones across individuals. Using synthetic and empirical TCR amino acid sequence data, we perform simulations to study expected clonal commonalities across multiple individuals. Based on our formulae, we compare these simulated results with the analytically predicted mean and variances of the repertoire overlap. Complementing the results on simulated repertoires, we derive explicit expressions for the richness and its uncertainty for specific, single-parameter truncated power-law probability distributions. Finally, the information loss associated with grouping together certain receptor sequences, as is done in spectratyping, is also evaluated. Our approach can be, in principle, applied under more general and mechanistically realistic clone generation models.

Indexed as

Mathematical ConceptsModels, BiologicalAmino Acid SequenceB-LymphocytesHumansModels, StatisticalDiversityOverlapPublic/private clonesSamplingT cell repertoire

Identifiers

PMID37707621
PMCPMC10501991

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.