《生命科学》 2025, 37(1): 26-36

计算生物学前沿进展及其应用态势分析

江　源¹ , 袁银池¹ , 李　虹^2,3 , 刘樱霞¹ , 江洪波^1,3 , 毛开云^1,*

¹中国科学院上海生命科学信息中心，中国科学院上海营养与健康研究所，上海 200031 ²中国科学院上海营养与健康研究所，上海 200031 ³中国科学院大学，北京 100049

摘　要：

计算思维与技术已成为生命科学研究的关键因素，促进了计算机科学与生物学间的融合。计算生物学推动科学家采用新方法建模、分析及解释，利用计算工具深化科学知识。计算生物学研究从基因调控解码到细胞信号转导理解，有望引领开创性发现。2024 年，计算生物学在分子( 基因组、RNA、蛋白质)模型、细胞图谱和空间组学等领域获得了很大突破。同时，研发投入的持续增加和个性化药物需求的不断攀升，共同推动了相关市场的蓬勃发展。然而，当前的计算生物学尚未构建起一个相对完备的研究体系。众多计算生物学的方法和理论尚待完善，面对更为复杂的生物学问题，科学家们仍在寻找合适的计算手段和方法以开展深入研究。

通讯作者：毛开云 , Email:kymao@sinh.ac.cn

Analysis of frontier progress and application trends in computational biology

JIANG Yuan¹ , YUAN Yin-Chi¹ , LI Hong^2,3 , LIU Ying-Xia¹ , JIANG Hong-Bo^1,3 , MAO Kai-Yun^1,*

¹Shanghai Information Center for Life Sciences, Shanghai Institute of Nutrition and Health, Chinese Academy of Science, Shanghai 200031, China ²Shanghai Institute of Nutrition and Health, Chinese Academy of Science, Shanghai 200031, China ³University of Chinese Academy of Sciences, Beijing 100049, China

Abstract:

Advances in computational methods and technologies have become essential in life science research, driving the integration of computer science and biology. These developments have enabled researchers to adopt innovative approaches for modeling, analyzing, and interpreting complex biological data, significantly enhancing scientific understanding. From decoding gene regulation to elucidating cell signaling pathways, computational biology holds the promise of transformative discoveries. By 2024, significant breakthroughs have been achieved in molecular biology—encompassing genome modeling, RNA, and protein—as well as in the development of cell atlases and spatial omics. Concurrently, increased investment in research and development, coupled with the growing demand for personalized medicine, has spurred rapid growth in related markets. Nevertheless, computational biology has yet to establish a comprehensive and cohesive research framework. Many methodologies and theoretical foundations remain underdeveloped, presenting challenges as researchers confront increasingly complex biological problems. Ongoing efforts aim to refine computational approaches and identify novel strategies to enable deeper and more impactful investigations in the field.

Communication Author：MAO Kai-Yun , Email:kymao@sinh.ac.cn