Evidence map›Paper›PMID 31020723›Full record

ArticleProtein science : a publication of the Protein Society2019

AbRSA: A robust tool for antibody numbering.

Lei Li, Shuang Chen, Zhichao Miao, Yang Liu, Xu Liu, Zhi-Xiong Xiao, Yang Cao

Abstract read
In one paragraph

Article in Protein science : a publication of the Protein Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing 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

40 citing papers in PubMed.

  1. Recombinant Protein Drugs: A 2025 Update.BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy · 2026
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  15. Unlocking the potential ofFrontiers in bioinformatics · 2025
    Review
  16. 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

7 authors.

Lei LiCenter of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, People's Republic of China.
Shuang ChenChengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, People's Republic of China.
Zhichao MiaoEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, CB10 1SD, United Kingdom.
Yang LiuCenter of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, People's Republic of China.
Xu LiuCenter of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, People's Republic of China.
Zhi-Xiong XiaoCenter of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, People's Republic of China.
Yang CaoCenter of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, People's Republic of China.ORCID 0000-0002-1925-2123

Funding

Wellcome TrustWellcome Trust nr. 108437/Z/15/Z
6 · The paper itself

Abstract

The remarkable progress in cancer immunotherapy in recent years has led to the heat of great development for therapeutic antibodies. Antibody numbering, which standardizes a residue index at each position of an antibody variable domain, is an important step in immunoinformatic analysis. It provides an equivalent index for the comparison of sequences or structures, which is particularly valuable for antibody modeling and engineering. However, due to the extremely high diversity of antibody sequences, antibody-numbering tools cannot work in all cases. This article introduces a new antibody-numbering tool named AbRSA, which integrates heuristic knowledge of region-specific features into sequence mapping to enhance the robustness. The benchmarks demonstrate that, AbRSA exhibits robust performance in numbering sequences with diverse lengths and patterns compared with the state-of-the-art tools. AbRSA offers a user-friendly interface for antibody numbering, complementarity-determining region delimitation, and 3D structure rendering. It is freely available at http://cao.labshare.cn/AbRSA.

Indexed as

SoftwareAmino Acid SequenceAntibodiesComplementarity Determining RegionsComputational BiologyHumansModels, MolecularAntibodiesComplementarity Determining Regionsantibodyantibody numberingcomplementarity-determining regionimmunoinformatic

Identifiers

PMID31020723
PMCPMC6635766

What OpenQuestion holds

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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.