Mathematical Modeling of Complex Biological Systems
Mathematical Modeling of Complex Biological Systems
复制标题
复杂生物系统的数学建模
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
H. Fischer
中科院分区：
文献类型：
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作者：
H. Fischer
要了解细胞、组织甚至人体等复杂的生物系统，仅识别和表征系统中的各个分子是不够的。还有必要彻底了解分子和途径之间的相互作用。对于理解癌症、阿尔茨海默病或酗酒等复杂疾病来说更是如此。随着最近的技术进步使研究人员能够在分子水平上监测复杂的细胞过程，焦点正在转向解释这些所谓的“组学”技术生成的数据。数学模型使研究人员能够研究复杂的调节过程如何相互联系以及这些过程的破坏如何导致疾病的发展。此外，计算模型帮助研究人员系统地分析系统扰动，提出假设来指导新实验测试的设计，并最终评估特定分子作为新治疗靶点的适用性。人们已经开发了许多数学方法来解决不同类别的生物过程，例如代谢过程或信号传导和调节途径。如今，建模方法对于生物学家来说至关重要，使他们能够分析复杂的生理过程，对于制药行业来说也是如此，作为支持药物发现和开发项目的手段。
To understand complex biological systems such as cells, tissues, or even the human body, it is not sufficient to identify and characterize the individual molecules in the system. It also is necessary to obtain a thorough understanding of the interaction between molecules and pathways. This is even truer for understanding complex diseases such as cancer, Alzheimer’s disease, or alcoholism. With recent technological advances enabling researchers to monitor complex cellular processes on the molecular level, the focus is shifting toward interpreting the data generated by these so-called “–omics” technologies. Mathematical models allow researchers to investigate how complex regulatory processes are connected and how disruptions of these processes may contribute to the development of disease. In addition, computational models help investigators to systematically analyze systems perturbations, develop hypotheses to guide the design of new experimental tests, and ultimately assess the suitability of specific molecules as novel therapeutic targets. Numerous mathematical methods have been developed to address different categories of biological processes, such as metabolic processes or signaling and regulatory pathways. Today, modeling approaches are essential for biologists, enabling them to analyze complex physiological processes, as well as for the pharmaceutical industry, as a means for supporting drug discovery and development programs.