生物信息学的大型语言模型
Wei Ruan1, Yanjun Lyu2, Jing Zhang2
1School of Computing University of Georgia Athens Georgia USA.
Quantitative biology (Beijing, China)
|February 12, 2026
概括
生物信息学特定语言模型 (BioLMs) 正在迅速发展,为疾病诊断和药物发现提供了新的工具. 本综述分析了BioLM的演变,应用,挑战和生物信息学的未来方向.
科学领域:
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
- 人工智能在医学中的应用
背景情况:
- 大型语言模型 (LLM) 正在迅速发展.
- 生物信息学特定语言模型 (BioLMs) 正在成为强大的工具.
- 需要对BioLM进行全面的分析.
研究的目的:
- 提供对BioLMs.的彻底审查.
- 分析它们的演变,分类和特征.
- 检查培训方法,数据集和评估框架.
主要方法:
- 文献综述和对现有BioLMs的分析.
- 基于架构和应用的BioLMs的分类.
- 检查培训数据,计算方法和评估指标.
主要成果:
- 生物LM在疾病诊断,药物发现和疫苗开发方面具有多样化的应用.
- 关键的挑战包括数据隐私,可解释性,偏见和域调整.
- 新兴趋势指向更复杂的生物和临床应用.
结论:
- 生物信息学在生物信息学和临床实践中具有变革性的潜力.
- 应对挑战对于负责任的开发和部署至关重要.
- 未来的研究应该专注于为复杂的生物问题推进生物LM.
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