Evidence map›Paper›PMID 32182714›Full record

ArticleBiomolecules2020

Machine Learning-Guided Prediction of Antigen-Reactive In Silico Clonotypes Based on Changes in Clonal Abundance through Bio-Panning.

Duck Kyun Yoo, Seung Ryul Lee, Yushin Jung, Haejun Han, Hwa Kyoung Lee, Jerome Han, Soohyun Kim, Jisu Chae, Taehoon Ryu, Junho Chung

Open access · goldAbstract read
In one paragraph

Article in Biomolecules, 2020. 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
0.8field-weighted citation impact, top 25% 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

5 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
  2. Article
  3. Stereotypic neutralizing VScience translational medicine · 2021
    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

10 authors at 1 institution in 1 country.

Duck Kyun YooDepartment of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul 03080, Korea.
Seung Ryul LeeDepartment of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul 03080, Korea.
Yushin JungCelemics, Inc., 131 Gasandigital 1-ro, Geumcheon-gu, Seoul 08506, Korea.
Haejun HanCelemics, Inc., 131 Gasandigital 1-ro, Geumcheon-gu, Seoul 08506, Korea.
Hwa Kyoung LeeDepartment of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul 03080, Korea.
Jerome HanDepartment of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul 03080, Korea.
Soohyun KimDepartment of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul 03080, Korea.
Jisu ChaeDepartment of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul 03080, Korea.
Taehoon RyuCelemics, Inc., 131 Gasandigital 1-ro, Geumcheon-gu, Seoul 08506, Korea.
Junho ChungDepartment of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul 03080, Korea.
Seoul National University · KR

Funding

Korea Drug Development Fund KDDF-201904-19
6 · The paper itself

Abstract

c-Met is a promising target in cancer therapy for its intrinsic oncogenic properties. However, there are currently no c-Met-specific inhibitors available in the clinic. Antibodies blocking the interaction with its only known ligand, hepatocyte growth factor, and/or inducing receptor internalization have been clinically tested. To explore other therapeutic antibody mechanisms like Fc-mediated effector function, bispecific T cell engagement, and chimeric antigen T cell receptors, a diverse panel of antibodies is essential. We prepared a chicken immune scFv library, performed four rounds of bio-panning, obtained 641 clones using a high-throughput clonal retrieval system (TrueRepertoire

Indexed as

Avian ProteinsChickensCloning, MolecularMachine LearningSequence Analysis, DNASingle-Chain AntibodiesAnimalsAntigensAntigensAvian ProteinsSingle-Chain Antibodiesantibody discoveryc-Metmachine learningnext-generation sequencingphage displayrandom forest

Identifiers

PMID32182714
PMCPMC7175295
OpenAlexW3009610687

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.