title: Hematopoiesis and its disorders: a systems biology approach.
abstract: 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.
authors.affiliation: Departments of Pediatrics and Cell and Molecular Biology, Children's Memorial Hospital and the Robert H. Lurie Comprehensive Cancer Center, Northwestern University School of Medicine, Chicago, IL 60611, USA.
authors.forename: Zakary L
authors.initials: ZL
authors.lastname: Whichard
authors.forename: Casim A
authors.initials: CA
authors.lastname: Sarkar
authors.forename: Marek
authors.initials: M
authors.lastname: Kimmel
authors.forename: Seth J
authors.initials: SJ
authors.lastname: Corey
mesh_terms: D006402:Hematologic Diseases / Q000503:physiopathology*; D006410:Hematopoiesis / Q000502:physiology*; D006801:Humans; D008954:Models, Biological; D049490:Systems Biology