Evidence map›Paper›PMID 28336958›Full record

ReviewExperimental & molecular medicine2017

From rabbit antibody repertoires to rabbit monoclonal antibodies.

Justus Weber, Haiyong Peng, Christoph Rader

Open access · goldAbstract readReview
In one paragraph

Review in Experimental & molecular medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 92 papers.

0numbers the graph read from it
0cells of the map it votes in
92citing papers in PubMed
9.6field-weighted citation impact, top 1% 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

92 citing papers in PubMed, 169 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Technologies for Monoclonal Antibody Discovery and Development.International journal of molecular sciences · 2025
    Review
  10. Contributions of large and agricultural animal models to immunology.Journal of immunology (Baltimore, Md. : 1950) · 2025
    Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Review
  16. Review
  17. Review
  18. Review
  19. Article
  20. Article

32 more citing papers are in PubMed but not listed here.

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 at 1 institution in 1 country.

Justus WeberDepartment of Immunology and Microbiology, The Scripps Research Institute, Jupiter, FL, USA.
Haiyong PengDepartment of Immunology and Microbiology, The Scripps Research Institute, Jupiter, FL, USA.
Christoph RaderDepartment of Immunology and Microbiology, The Scripps Research Institute, Jupiter, FL, USA.
Scripps Research Institute · US

Funding

Novel Enediyne-Based Antibody-Drug Conjugates for CancersR01CA204484 · NCI · UNIVERSITY OF FLORIDA · PI Natarajan Muthusamy, Ben Shen · 2017 to 2026
$4.6M
Chemically Programmed Bispecific Antibodies for Cancer TherapyR01CA181258 · NCI · SCRIPPS FLORIDA · PI RADER, CHRISTOPH · 2014 to 2018
$2.0M
NCI NIH HHS R01 CA181258NCI NIH HHS R01 CA204484
6 · The paper itself

Abstract

In this review, we explain why and how rabbit monoclonal antibodies have become outstanding reagents for laboratory research and increasingly for diagnostic and therapeutic applications. Starting with the unique ontogeny of rabbit B cells that affords highly distinctive antibody repertoires rich in in vivo pruned binders of high diversity, affinity and specificity, we describe the generation of rabbit monoclonal antibodies by hybridoma technology, phage display and alternative methods, along with an account of successful humanization strategies.

Indexed as

AnimalsAntibodies, Monoclonal, HumanizedHumansImmunologic TechniquesRabbitsAntibodies, Monoclonal, Humanized

Identifiers

PMID28336958
PMCPMC5382564
OpenAlexW2598879757

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.