Evidence map›Paper›PMID 28898398›Full record

ReviewImmunology2018

Integrating high-throughput screening and sequencing for monoclonal antibody discovery and engineering.

Cristina Parola, Daniel Neumeier, Sai T Reddy

Abstract readReview
In one paragraph

Review in Immunology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.

0numbers the graph read from it
0cells of the map it votes in
57citing 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

57 citing papers in PubMed.

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  14. Tumor biomarkers for diagnosis, prognosis and targeted therapy.Signal transduction and targeted therapy · 2024
    Review
  15. Peptide Antibodies: Current Status.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  16. Review
  17. Article
  18. 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

3 authors.

Cristina ParolaDepartment of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Daniel NeumeierDepartment of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Sai T ReddyDepartment of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.ORCID 0000-0002-9177-0857

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Monoclonal antibody discovery and engineering is a field that has traditionally been dominated by high-throughput screening platforms (e.g. hybridomas and surface display). In recent years the emergence of high-throughput sequencing has made it possible to obtain large-scale information on antibody repertoire diversity. Additionally, it has now become more routine to perform high-throughput sequencing on antibody repertoires to also directly discover antibodies. In this review, we provide an overview of the progress in this field to date and show how high-throughput screening and sequencing are converging to deliver powerful new workflows for monoclonal antibody discovery and engineering.

Indexed as

Drug DiscoveryGenetic EngineeringHigh-Throughput Nucleotide SequencingHigh-Throughput Screening AssaysAnimalsAntibodies, MonoclonalHumansAntibodies, Monoclonalantibodiesbioinformaticshigh-throughput sequencingsurface display

Identifiers

PMID28898398
PMCPMC5721244

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.