Evidence map›Paper›PMID 24423623›Full record

ArticlemAbs

The antibody mining toolbox: an open source tool for the rapid analysis of antibody repertoires.

Sara D'Angelo, Jacob Glanville, Fortunato Ferrara, Leslie Naranjo, Cheryl D Gleasner, Xiaohong Shen, Andrew R M Bradbury, Csaba Kiss

Open access · goldAbstract read
In one paragraph

Article in mAbs. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
4.8field-weighted citation impact, top 5% 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

32 citing papers in PubMed, 42 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Intrathecal B-cell activation in LGI1 antibody encephalitis.Neurology(R) neuroimmunology & neuroinflammation · 2020
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Analyzing Immunoglobulin Repertoires.Frontiers in immunology · 2018
    Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Ligand-targeted theranostic nanomedicines against cancer.Journal of controlled release : official journal of the Controlled Release Society · 2016
    Review
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

8 authors at 4 institutions in 1 country.

Sara D'AngeloNew Mexico Consortium; Los Alamos, NM, USA.
Jacob GlanvilleStanford Immunology; Stanford University; Stanford, CA USA.
Fortunato FerraraNew Mexico Consortium; Los Alamos, NM, USA.
Leslie NaranjoB Division; Los Alamos National Laboratory; Los Alamos, NM USA.
Cheryl D GleasnerB Division; Los Alamos National Laboratory; Los Alamos, NM USA.
Xiaohong ShenB Division; Los Alamos National Laboratory; Los Alamos, NM USA.
Andrew R M BradburyB Division; Los Alamos National Laboratory; Los Alamos, NM USA.
Csaba KissB Division; Los Alamos National Laboratory; Los Alamos, NM USA.
Los Alamos Medical Center · USNew Mexico Consortium · USLos Alamos National Laboratory · USStanford Medicine · US

Funding

A high throughput pipeline to select renewable recombinant polyclonal antibodiesU54DK093500 · NIDDK · LOS ALAMOS NAT SECTY-LOS ALAMOS NAT LAB · PI BRADBURY, ANDREW · 2011 to 2013
$4.4M
NIDDK NIH HHS 5U54DK093500-02NIDDK NIH HHS U54 DK093500
6 · The paper itself

Abstract

In vitro selection has been an essential tool in the development of recombinant antibodies against various antigen targets. Deep sequencing has recently been gaining ground as an alternative and valuable method to analyze such antibody selections. The analysis provides a novel and extremely detailed view of selected antibody populations, and allows the identification of specific antibodies using only sequencing data, potentially eliminating the need for expensive and laborious low-throughput screening methods such as enzyme-linked immunosorbant assay. The high cost and the need for bioinformatics experts and powerful computer clusters, however, have limited the general use of deep sequencing in antibody selections. Here, we describe the AbMining ToolBox, an open source software package for the straightforward analysis of antibody libraries sequenced by the three main next generation sequencing platforms (454, Ion Torrent, MiSeq). The ToolBox is able to identify heavy chain CDR3s as effectively as more computationally intense software, and can be easily adapted to analyze other portions of antibody variable genes, as well as the selection outputs of libraries based on different scaffolds. The software runs on all common operating systems (Microsoft Windows, Mac OS X, Linux), on standard personal computers, and sequence analysis of 1-2 million reads can be accomplished in 10-15 min, a fraction of the time of competing software. Use of the ToolBox will allow the average researcher to incorporate deep sequence analysis into routine selections from antibody display libraries.

Indexed as

SoftwareComplementarity Determining RegionsHumansSequence Analysis, DNASingle-Chain AntibodiesComplementarity Determining RegionsSingle-Chain AntibodiesAbMining ToolBoxantibody librarydeep sequencingHCDR3regular expression

Identifiers

PMID24423623
PMCPMC3929439
OpenAlexW2042786738

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.