ReviewComputational and structural biotechnology journal2022
Research progress of reduced amino acid alphabets in protein analysis and prediction.
Review in Computational and structural biotechnology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed.
- Quantitative analysis of trafficking defects induced by heterozygous expression of hERG voltage sensor domain variants.Channels (Austin, Tex.) · 2026Article
- Artificial intelligence aided design of peptides with custom secondary structure motifs and reduced amino acid alphabets.bioRxiv : the preprint server for biology · 2026Article
- GBSC: graph-based sequence clustering method for similar short tandem repeats in protein sequences.Bioinformatics (Oxford, England) · 2026Article
- Optimizing protein tokenization: reduced amino acid alphabets for efficient and accurate protein language models.Bioinformatics (Oxford, England) · 2026Article
- Plant-associated fungi co-opt ancient antimicrobials for host manipulation.Science advances · 2026Article
- Ab-SELDON: Leveraging Diversity Data for an Efficient Automated Computational Pipeline for Antibody Design.Journal of chemical information and modeling · 2026Article
- Graph attention with structural features improves the generalizability of identifying functional sequences at a protein interface.bioRxiv : the preprint server for biology · 2025Article
- Uncovering differential tolerance to deletions versus substitutions with a protein language model.Cell systems · 2025Article
- A transcriptomic and proteomic analysis and comparison of human brain tissue from patients with and without epilepsy.Scientific reports · 2025Article
- Review
- Exploring Potential Diagnostic Biomarkers for Mechanical Asphyxia in the Heart Based on Proteomics Technology.International journal of molecular sciences · 2024Article
- Lambda3: homology search for protein, nucleotide, and bisulfite-converted sequences.Bioinformatics (Oxford, England) · 2024Article
- Protein language models meet reduced amino acid alphabets.Bioinformatics (Oxford, England) · 2024Article
- Snekmer: a scalable pipeline for protein sequence fingerprinting based on amino acid recoding.Bioinformatics advances · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Proteins are the executors of cellular physiological activities, and accurate structural and function elucidation are crucial for the refined mapping of proteins. As a feature engineering method, the reduction of amino acid composition is not only an important method for protein structure and function analysis, but also opens a broad horizon for the complex field of machine learning. Representing sequences with fewer amino acid types greatly reduces the complexity and noise of traditional feature engineering in dimension, and provides more interpretable predictive models for machine learning to capture key features. In this paper, we systematically reviewed the strategy and method studies of the reduced amino acid (RAA) alphabets, and summarized its main research in protein sequence alignment, functional classification, and prediction of structural properties, respectively. In the end, we gave a comprehensive analysis of 672 RAA alphabets from 74 reduction methods.
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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.