TRAFICA:一个开放的染色体语言模型来改善转录因子绑定亲和度预测
Yu Xu1, Chonghao Wang1, Ke Xu1
1Department of Computer Science, Hong Kong Baptist University, Kowloon Town, Hong Kong, China.
Bioinformatics (Oxford, England)
|August 23, 2025
概括
我们开发了TRAFICA,一个开放的染色体语言模型, TRAFICA集成了体内开放的染色体数据,优于现有的TF-DNA相互作用预测方法.
科学领域:
- 基因组学
- 计算生物学
- 生物信息学
背景情况:
- 在转录因子和DNA (TF-DNA) 的结合亲和力预测对于理解基因调节至关重要.
- 目前的工具往往忽略了开放色素区域的体内TF结合偏好,仅依赖体内数据.
- 这种局限性阻碍了TF-DNA相互作用在它们的原生细胞环境中的准确预测.
研究的目的:
- 开发一个先进的计算模型来预测TF-DNA结合亲和力.
- 将体内开放的染色体区域的序列特征纳入结合 afinity 的预测.
- 提高TF-DNA结合预测的准确性和生物相关性.
主要方法:
- 开发了TRAFICA,一个开放的染色体语言模型.
- 从ATAC-seq实验中预先训练了超过280万个核酸序列,以了解体内TF结合偏好.
- 在PBM和HT-SELEXTF-DNA结合配置上使用低级适应 (LoRA) 微调的TRAFICA.
主要成果:
- TRAFICA显著超过现有的预测工具和先进的DNA语言模型.
- 在体外和体外预测TF-DNA结合亲和力方面取得了最先进的性能.
- 证明了结合开放色素序列特征以改善预测的重要性.
结论:
- 考虑开放色素区域的序列特征显著提高了TF-DNA结合亲和力的预测.
- TRAFICA代表了一种更准确的TF-DNA相互作用建模的新方法.
- 这些发现为通过改进的TF-DNA结合预测更好地理解基因调节铺平了道路.
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