markdown AI 驱动的生物医学研究迎来新突破。 近日，美国索尔克研究所开发出名为 ShortStop 的机器学习框架，该工具专注于探索长期以来被忽视的基因组区域，特别是那些可能编码微蛋白的 小开放阅读框（smORF） 。这项研究成果发表于《BMC方法学》期刊，标志着人工智能在加速生物医学研究，特别是疾病研究中的重要进展。

研究人员针对微蛋白 (smORFs)功能鉴定难题，开发了ShortStop机器学习框架。该研究通过构建人工合成序列PRISMs作为负对照，结合Swiss-Prot已知微蛋白特征，实现了90%以上准确率的分类（SAMs/PRISMs），成功发现被传统方法遗漏的StARuMP等功能性微蛋白，为癌症等疾病研究提供了新靶点筛选工具。

美国索尔克研究所开发出一种名为ShortStop的机器学习框架，用于探索以往“被忽视的DNA区域”，寻找在疾病中发挥关键作用的微蛋白。相关研究发表在最新一期《BMC方法学》上。

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