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2026
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| Acceso en línea: | https://doi.org/10.5281/zenodo.18229121 |
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| _version_ | 1866901194709925888 |
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| author | Damon, Kyron |
| author_facet | Damon, Kyron |
| contents | <p>The paper demonstrates that a single, fixed Ricker (Mexican-hat) wavelet, applied to mean-centered hydrophobicity sequences, produces statistically significant enrichment of long-range residue contacts in a subset of proteins whose folding is dominated by hydrophobic collapse. The method uses no per-protein tuning and is evaluated against a benchmark that includes both collapse-dominated proteins and mechanism-mismatched stress tests (e.g. disulfide-rich and membrane-associated structures).</p> <p> </p> <p>Key findings include:</p> <p> </p> <ul> <li>Emergence of a characteristic coherence scale in sequence space</li> <li>Order-of-magnitude enrichment of true long-range contacts in collapse-dominated proteins</li> <li>Clear mechanism specificity: the method succeeds selectively rather than universally</li> </ul> <p> </p> <p> </p> <p>The accompanying code package reproduces all figures and statistics reported in the manuscript, including:</p> <p> </p> <ul> <li>Kernel convolution and response rectification</li> <li>Contact enrichment and precision-lift metrics</li> <li>Benchmark and stress-test analyses </li> </ul> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18229121 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Pre-dynamical Ordering in Protein Folding via Fixed-Kernel Convolution Damon, Kyron Protein folding Hydrophobic collapse Convolution kernel Signal processing Non-iterative methods Computational biophysics Contact map prediction Self organisation Emergent structure <p>The paper demonstrates that a single, fixed Ricker (Mexican-hat) wavelet, applied to mean-centered hydrophobicity sequences, produces statistically significant enrichment of long-range residue contacts in a subset of proteins whose folding is dominated by hydrophobic collapse. The method uses no per-protein tuning and is evaluated against a benchmark that includes both collapse-dominated proteins and mechanism-mismatched stress tests (e.g. disulfide-rich and membrane-associated structures).</p> <p> </p> <p>Key findings include:</p> <p> </p> <ul> <li>Emergence of a characteristic coherence scale in sequence space</li> <li>Order-of-magnitude enrichment of true long-range contacts in collapse-dominated proteins</li> <li>Clear mechanism specificity: the method succeeds selectively rather than universally</li> </ul> <p> </p> <p> </p> <p>The accompanying code package reproduces all figures and statistics reported in the manuscript, including:</p> <p> </p> <ul> <li>Kernel convolution and response rectification</li> <li>Contact enrichment and precision-lift metrics</li> <li>Benchmark and stress-test analyses </li> </ul> |
| title | Pre-dynamical Ordering in Protein Folding via Fixed-Kernel Convolution |
| topic | Protein folding Hydrophobic collapse Convolution kernel Signal processing Non-iterative methods Computational biophysics Contact map prediction Self organisation Emergent structure |
| url | https://doi.org/10.5281/zenodo.18229121 |