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        <datestamp>2026-09-28T11:40:43Z</datestamp>
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          <dc:title>Supplementary Datasets and Data-Package for &lt;b&gt;&lt;i&gt;CRISPR-enhanced assessment of variants of unknown significance nominates oncology therapeutic targets and drug repositioning opportunities&lt;/i&gt;&lt;/b&gt; Savino et Al. 2026</dc:title>
          <dc:creator>Francesco Iorio (6370019)</dc:creator>
          <dc:subject>Bioinformatic methods development</dc:subject>
          <dc:subject>Genomics and transcriptomics</dc:subject>
          <dc:subject>Statistical and quantitative genetics</dc:subject>
          <dc:subject>tested variants</dc:subject>
          <dc:subject>decoy set</dc:subject>
          <dc:description>&lt;p dir="ltr"&gt;This repository contains supplementary datasets and the data package required to reproduce the analysis, results, and figures presented in Savino et al. (2026).&lt;br&gt;&lt;br&gt;The study leverages CRISPR-based functional genomics to systematically evaluate Variants of Unknown Significance (VUS) in oncology, identifying actionable therapeutic targets and highlighting novel opportunities for drug repositioning.&lt;br&gt;&lt;br&gt;The complete computational workflow is available at https://github.com/francescojm/CRISPR-VUS.&lt;/p&gt;&lt;p dir="ltr"&gt;The repository contains a Jupyter notebook, accompanying R scripts, configuration files, software-environment information and instructions for reproducing the analyses and figures. The notebook can also be accessed through Google Colab (at https://colab.research.google.com/drive/1PkduxjbHQH4zZxk3g69LWQUGL_jsL-aq?usp=sharing).&lt;/p&gt;&lt;p&gt;&lt;br&gt;&lt;/p&gt;</dc:description>
          <dc:date>2026-09-28T11:40:43Z</dc:date>
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          <dc:identifier>10.6084/m9.figshare.33435853.v6</dc:identifier>
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