ArticleBMB reports2026
CodonMutator: a python-based automated oligonucleotide design framework for deep mutational scanning library construction.
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.
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.
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.
Who cites it
1 citing paper in PubMed.
- Functional dissection ofProceedings of the National Academy of Sciences of the United States of America · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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
Identifiers
41407322PMC12936597What OpenQuestion holds
Registered trials
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.