ArticleProteins2024
Application of artificial intelligence and machine learning techniques to the analysis of dynamic protein sequences.
Article in Proteins, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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.
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Who cites it
3 citing papers in PubMed.
- Stabilization strategies and advancements in lyophilization to preserve integrity and efficacy of next-generation biologicals.International journal of pharmaceutics: X · 2026Review
- The Spatial Distribution of Local Mobility in Folded Proteins.The journal of physical chemistry. B · 2026Article
- Techniques for Bioinformatic Applications in Protein Dynamics.Methods in molecular biology (Clifton, N.J.) · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
We apply methods of Artificial Intelligence and Machine Learning to protein dynamic bioinformatics. We rewrite the sequences of a large protein data set, containing both folded and intrinsically disordered molecules, using a representation developed previously, which encodes the intrinsic dynamic properties of the naturally occurring amino acids. We Fourier analyze the resulting sequences. It is demonstrated that classification models built using several different supervised learning methods are able to successfully distinguish folded from intrinsically disordered proteins from sequence alone. It is further shown that the most important sequence property for this discrimination is the sequence mobility, which is the sequence averaged value of the residue-specific average alpha carbon B factor. This is in agreement with previous work, in which we have demonstrated the central role played by the sequence mobility in protein dynamic bioinformatics and biophysics. This finding opens a path to the application of dynamic bioinformatics, in combination with machine learning algorithms, to a range of significant biomedical problems.
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Registered trials
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