ReviewTrends in biotechnology2011
Deep mutational scanning: assessing protein function on a massive scale.
Review in Trends in biotechnology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 134 papers.
What it found
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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.
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Who cites it
134 citing papers in PubMed.
- Strain-specific epistasis shapes fitness landscapes of APOBEC3G antagonism by HIV-1 Vif proteins.Science advances · 2026Article
- Scanning the horizon: deep mutational scanning approaches in virology.Journal of virology · 2026Review
- How far can you go? Extrapolating values of catalytic activity from known protein landscapes in natural and directed evolution.Chemical Society reviews · 2026Review
- Diverse mechanisms of translation arrest by a Clostridia ribosome stalling peptide CliM.Nature communications · 2026Article
- Directed evolution of enzymes at the crossroads of tradition and innovation.FEBS open bio · 2026Review
- Deep mutational scan of the pore of the cold-sensing TRPM8 channel.bioRxiv : the preprint server for biology · 2026Article
- HaloTag-based approach to quantify subcellular localization of TRPV3 channels.Biophysical journal · 2026Article
- Learning a viral protein's vocabulary.Nature ecology & evolution · 2026Article
- Decoding the substrate specificity landscape of a promiscuous enzyme through multi-substrate mutational scanning.Nature communications · 2026Article
- Accurate variant effect estimation in FACS-based deep mutational scanning data with Lilace.Genome biology · 2026Article
- Article
- EZ-DMS - A Simple and Accessible Protocol and Software Package for Deep Mutational Scanning of Virus Proteins.bioRxiv : the preprint server for biology · 2026Article
- MiLaSol: modeling protein solubility by mixing up multiple protein language models.Bioinformatics advances · 2026Article
- Engineering a Bright Near-Infrared Fluorescent Protein by Screening a Comprehensive Phenotypic Landscape.bioRxiv : the preprint server for biology · 2025Article
- Activity-based selection for enhanced base editor mutational scanning.Nature genetics · 2025Article
- Insights from deep mutational scanning in the context of an emerging pathogen.Biochemical Society transactions · 2025Review
- A protein dynamics-based deep learning model enhances predictions of fitness and epistasis.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Fitness Landscapes of APOBEC3G Antagonism by HIV-1 Vif proteins.bioRxiv : the preprint server for biology · 2025Article
- Deep Mutational Scanning in Immunology: Techniques and Applications.Pathogens (Basel, Switzerland) · 2025Review
- The Role of AI-Driven De Novo Protein Design in the Exploration of the Protein Functional Universe.Biology · 2025Review
74 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Analysis of protein mutants is an effective means to understand their function. Protein display is an approach that allows large numbers of mutants of a protein to be selected based on their activity, but only a handful with maximal activity have been traditionally identified for subsequent functional analysis. However, the recent application of high-throughput sequencing (HTS) to protein display and selection has enabled simultaneous assessment of the function of hundreds of thousands of mutants that span the activity range from high to low. Such deep mutational scanning approaches are rapid and inexpensive with the potential for broad utility. In this review, we discuss the emergence of deep mutational scanning, the challenges associated with its use and some of its exciting applications.
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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.