Evidence map›Paper›PMID 41407322›Full record

ArticleBMB reports2026

CodonMutator: a python-based automated oligonucleotide design framework for deep mutational scanning library construction.

Jeongha Lee, Seong Kyoon Park, Byung Joon Hwang, Murim Choi

Abstract read
In one paragraph

Article in BMB reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Functional dissection ofProceedings of the National Academy of Sciences of the United States of America · 2026
    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

4 authors.

Jeongha LeeDepartment of Brain Sciences, Daegu Gyeongbuk Institute of Science & Technology (DGIST), Daegu 42988, Korea.
Seong Kyoon ParkDepartment of Molecular Bioscience, College of Biomedical Science, Kangwon National University, Chuncheon 24341, Korea.
Byung Joon HwangDepartment of Molecular Bioscience, College of Biomedical Science, Kangwon National University, Chuncheon 24341, Korea; Nabigene Inc., Kangwon Daehakgil, Chuncheon 24341, Korea.
Murim ChoiDepartment of Brain Sciences, Daegu Gyeongbuk Institute of Science & Technology (DGIST), Daegu 42988, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deep mutational scanning (DMS) enables systematic evaluation of protein sequence-function relationships, but its utility is often limited by the complexity of library construction. Existing mutagenesis strategies are either biased, labor-intensive, or prone to design errors, restricting their scalability for comprehensive variant generation. Here, we present a systematic cloning framework coupled with an automated Python-based pipeline for oligonucleotide design in DMS library construction. Our strategy employs restriction enzyme-guided tiling to partition coding sequences into manageable fragments, ensuring uniform coverage and compatibility with standard cloning workflows. The pipeline supports both strict and relaxed design modes, minimizes redundancy, and incorporates silent mutations to prevent restriction site conflicts. This platform optimizes library design efficiency, improves accuracy, and provides a flexible framework adaptable to diverse genes and experimental contexts. By integrating molecular cloning constraints with computational automation, our method offers a scalable and accessible solution to accelerate DMS library construction and functional genomics studies. [BMB Reports 2026; 59(2): 137-142].

Indexed as

Gene LibraryOligonucleotidesCloning, MolecularCodonHigh-Throughput Nucleotide SequencingMutagenesisMutationSoftwareCodonOligonucleotides

Identifiers

PMID41407322
PMCPMC12936597

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.