ArticlemAbs
Selection of target-binding proteins from the information of weakly enriched phage display libraries by deep sequencing and machine learning.
Article in mAbs. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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
9 citing papers in PubMed.
- Multidimensional maturation of antibody variable domains with machine-learning assistance.mAbs · 2026Article
- Phage Display as a Promising Platform for Peptide Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Artificial Intelligence in Bacteriophage Science: A Comprehensive Narrative Review of Applications, Challenges, and Translational Opportunities.Antibiotics (Basel, Switzerland) · 2026Review
- From randomness to recognition: modeling the evolution of DNA sequence information during enrichment for binding.Bioinformatics advances · 2026Article
- Article
- Phage Display Technology in Biomarker Identification with Emphasis on Non-Cancerous Diseases.Molecules (Basel, Switzerland) · 2024Review
- Development of a new affinity maturation protocol for the construction of an internalizing anti-nucleolin antibody library.Scientific reports · 2024Article
- Extensive antibody search with whole spectrum black-box optimization.Scientific reports · 2024Article
- Phage-based peptides for pancreatic cancer diagnosis and treatment: alternative approach.Frontiers in microbiology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite the advances in surface-display systems for directed evolution, variants with high affinity are not always enriched due to undesirable biases that increase target-unrelated variants during biopanning. Here, our goal was to design a library containing improved variants from the information of the "weakly enriched" library where functional variants were weakly enriched. Deep sequencing for the previous biopanning result, where no functional antibody mimetics were experimentally identified, revealed that weak enrichment was partly due to undesirable biases during phage infection and amplification steps. The clustering analysis of the deep sequencing data from appropriate steps revealed no distinct sequence patterns, but a Bayesian machine learning model trained with the selected deep sequencing data supplied nine clusters with distinct sequence patterns. Phage libraries were designed on the basis of the sequence patterns identified, and four improved variants with target-specific affinity (EC
Indexed as
Identifiers
What 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.