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Wolframin Degradome Foundation Atlas

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Figshare2025-09-18 更新2026-04-28 收录
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https://figshare.com/articles/dataset/Wolframin_Degradome_Foundation_Atlas/30150589
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Wolframin Degradome Foundation Atlas (Version 1):This open-access dataset presents Version 3 of the Wolframin Degradome Foundation Atlas, a comprehensive proteolytic peptide resource designed to support translational research in Wolfram Syndrome. This initial version (Wolframin_Degradome_Foundation_Atlas_v1.tar.gz) combines the degradomes for several Wolframin mutations in one single unified dataset with high-level compression, improving usability and download efficiency. These data may prove particularly valuable for clinical researchers developing or analyzing protein aggregation therapeutic strategies, such as therapeutically targetable peptides, antisense oligonucleotides, or for biomarker-based outcome measures in clinical trials.Each peptide entry includes a revised nomenclature that encodes the mutation type and cleavage start/stop positions relative to the full-length Wolframin sequence (e.g., "wolf-a684v-87-170" for a mutant fragment, "wolf-wt-12-160" for wild type). This standardization improves interpretability and facilitates statistical and bioinformatics analyses.The dataset is distributed as a tab-delimited ASCII (.txt) file for straightforward compatibility with statistical and computational pipelines. Due to the expanded data volume and detailed annotation, the file is compressed for efficiency. To extract, use the following command in a bash terminal:tar -xvJf Wolframin_Degradome_Foundation_Atlas_v3.tar.gzCodesDataset generation is fully reproducible using three open-source tools: Python, BLAST, and SAS. Accompanying scripts are included in the repository and are fully documented for transparency. Users are encouraged to adapt file paths and settings to their local environment. These scripts follow the methodology described in [1].References[1] Petzold A. Proteolysis-Based Biomarker Repertoire of the Neurofilament Proteome. J Neurochem. 2025 Mar;169(3):e70023.doi: 10.1111/jnc.70023. PMID: 40066701; PMCID: PMC11894590.
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2025-09-18
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