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Systems Hematology: An Introduction

机译:系统血液学:介绍

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Hematologists have traditionally studied blood and its components by simplifying it into its components and functions. A variety of new techniques have generated large and complex datasets. Coupled to an appreciation of blood as a dynamic system, a new approach in systems hematology is needed. Systems hematology embraces the multi-scale complexity with a combination of mathematical, engineering, and computational tools for constructing and validating models of biological phenomena. The validity of mathematical modeling in hematopoiesis was established early by the pioneering work of Till and McCulloch. This volume seeks to introduce to the various scientists and physicians to the multi-faceted field of hematology by highlighting recent works in systems biology. Deterministic, stochastic, statistical, and network-based models 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 drug resistance. Future advances require technological improvements in computing power, imaging, and proteomics as well as greater collaboration between experimentalists and modelers. Altogether, systems hematology will improve our understanding of normal and abnormal hematopoiesis, better define stem cells and their daughter cells, and potentially lead to more effective therapies.
机译:通过将其简化为其组件和功能,血液学师传统上研究了血液及其组件。各种新技术已生成大型和复杂的数据集。再加上血液作为动态系统的升值,需要一种在系统血液学中的新方法。系统血液学包括用于构建和验证生物现象模型的数学,工程和计算工具的组合,包括多尺度复杂性。血液缺陷中数学建模的有效性早期通过直到和麦克洛克的开创性工作建立。该卷旨在通过突出系统生物学中的最新作品,向各种科学家和医生介绍各种科学家和医生到多方面的血液结构领域。确定性,随机,统计和网络模型已被用于更好地理解血液缺陷的一系列主题,包括血细胞生产,周期性化学性蛋白的周期性,响应细胞因子给药的干细胞产生,以及耐药性的出现。未来的进步需要计算能力,成像和蛋白质组学的技术改进,以及实验主义者和建模者之间的更大合作。完全,系统血液学将改善我们对正常和异常血液缺陷的理解,更好地定义干细胞及其子细胞,并且可能导致更有效的疗法。

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