通过in silico方法破译调节细胞死亡子程序的规则
Lu Zhang1, Yingying Dai2, Qingzhu Li3
1Department of Dermatology & Venerology, West China Hospital, Sichuan University, Chengdu 610041, PR China; Laboratory of Dermatology, Clinical Institute of Inflammation and Immunology (CIII), Frontiers Science Center for Disease-related Molecular Network and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, PR China.
调控细胞死亡 (RCD) 的研究正在以in silico方法推进. 本综述强调了在线资源和计算方法,以加速发现各种疾病的治疗点.
科学领域:
- * 疾病研究中的计算生物学和生物信息学.
- * 跨学科的方法整合了omics和系统生物学.
背景情况:
- * 调节细胞死亡 (RCD) 对于发育和平衡至关重要,但其调节失调会导致癌症和神经退行等疾病.
- *调节RCD是一种治疗策略,在实验和计算研究方法方面取得了快速进展.
- *包括数据库,AI和ML在内的in silico方法正在加速RCD研究.
研究的目的:
- *为调节细胞死亡 (RCD) 的 in silico 方法提供全面的概述.
- * 促进在线资源的有效利用,以开发治疗干预措施.
- * 弥合计算工具和RCD研究之间的差距.
主要方法:
- *对RCD的in silico方法进行现有文献的审查和综合.
- * RCD相关数据库和计算工具的分类.
- *讨论人工智能,机器学习,多omics和系统生物学集成.
主要成果:
- * RCD 数据库是基础性的,提供了广泛的生物数据用于in silico分析.
- *人工智能和机器学习与多omics数据的集成使RCD监管网络的解码成为可能.
- * In silico 方法提高了疾病生物标志物和治疗点的发现.
结论:
- *在调节细胞死亡 (RCD) 研究的推进中,in silico方法是不可或缺的.
- * 多种计算方法的整合加速了新的治疗策略的识别.
- *持续开发和管理RCD数据库对于未来的发现至关重要.
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