Hematopoiesis and its disorders: a systems biology approach.
Hematopoiesis and its disorders: a systems biology approach.
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DOI：
10.1182/blood-2009-08-215798
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发表时间：
2010-03
期刊：
影响因子：
20.3
通讯作者：
Z. Whichard;Casim A. Sarkar;M. Kimmel;S. Corey
中科院分区：
文献类型：
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作者：
Z. Whichard;Casim A. Sarkar;M. Kimmel;S. Corey
传统上，科学家们通过将复杂的生物系统简化为简单的构建模块来研究它们。然而，基因组测序、高通量筛选和蛋白质组学产生了大量数据集，揭示了组分和相互作用的高度复杂性。系统生物学通过数学、工程和计算工具的组合来构建和验证生物现象的模型，从而拥抱这种复杂性。Till和McCulloch的开创性工作很早就确立了造血数学建模的有效性。在回顾最近的论文中，我们强调了确定性，随机性，统计学和基于网络的模型，这些模型已被用于更好地理解造血中的一系列主题，包括血细胞产生，周期性中性粒细胞减少症的周期性，干细胞生产响应于细胞因子管理，以及慢性髓细胞白血病中伊马替尼耐药的出现。未来的进步需要在计算能力、成像和蛋白质组学方面的技术改进，以及实验者和建模者之间更大的合作。总之，系统生物学将提高我们对正常和异常造血的理解，更好地定义干细胞及其子细胞，并可能导致更有效的治疗。
Scientists have traditionally studied complex biologic systems by reducing them to simple building blocks. Genome sequencing, high-throughput screening, and proteomics have, however, generated large datasets, revealing a high level of complexity in components and interactions. Systems biology embraces this complexity with a combination of mathematical, engineering, and computational tools for constructing and validating models of biologic phenomena. The validity of mathematical modeling in hematopoiesis was established early by the pioneering work of Till and McCulloch. In reviewing more recent papers, we highlight deterministic, stochastic, statistical, and network-based models that have been used to better understand a range of topics in hematopoiesis, including blood cell production, the periodicity of cyclical neutropenia, stem cell production in response to cytokine administration, and the emergence of imatinib resistance in chronic myeloid leukemia. Future advances require technologic improvements in computing power, imaging, and proteomics as well as greater collaboration between experimentalists and modelers. Altogether, systems biology will improve our understanding of normal and abnormal hematopoiesis, better define stem cells and their daughter cells, and potentially lead to more effective therapies.