Journal•ISSN: 1939-005X
Wiley Interdisciplinary Reviews: Systems Biology and Medicine
Wiley-Blackwell
About: Wiley Interdisciplinary Reviews: Systems Biology and Medicine is an academic journal. The journal publishes majorly in the area(s): Systems biology & Gene. It has an ISSN identifier of 1939-005X. Over the lifetime, 436 publications have been published receiving 16034 citations.
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TL;DR: This review focuses on the hierarchical structure of the hematopoietic system, the current understanding of microenvironment and molecular cues regulating self‐renewal and differentiation of adult HSCs, and the currently emerging systems approaches to understand HSC biology.
Abstract: The mammalian blood system, containing more than 10 distinct mature cell types, stands on one specific cell type, hematopoietic stem cell (HSC). Within the system, only HSCs possess the ability of both multipotency and self-renewal. Multipotency is the ability to differentiate into all functional blood cells. Self-renewal is the ability to give rise to HSC itself without differentiation. Since mature blood cells (MBCs) are predominantly short-lived, HSCs continuously provide more differentiated progenitors while properly maintaining the HSC pool size throughout life by precisely balancing self-renewal and differentiation. Thus, understanding the mechanisms of self-renewal and differentiation of HSC has been a central issue. In this review, we focus on the hierarchical structure of the hematopoietic system, the current understanding of microenvironment and molecular cues regulating self-renewal and differentiation of adult HSCs, and the currently emerging systems approaches to understand HSC biology.
734 citations
TL;DR: The nuclear factor kappa B (NFκB) family of transcription factors is a key regulator of immune development, immune responses, inflammation, and cancer as mentioned in this paper, which can reveal deeper insights about the regulatory design principles.
Abstract: The nuclear factor kappa B (NFκB) family of transcription factors is a key regulator of immune development, immune responses, inflammation, and cancer. The NFκB signaling system (defined by the interactions between NFκB dimers, IκB regulators, and IKK complexes) is responsive to a number of stimuli, and upon ligand-receptor engagement, distinct cellular outcomes, appropriate to the specific signal received, are set into motion. After almost three decades of study, many signaling mechanisms are well understood, rendering them amenable to mathematical modeling, which can reveal deeper insights about the regulatory design principles. While other reviews have focused on upstream, receptor proximal signaling (Hayden MS, Ghosh S. Signaling to NF-κB. Genes Dev 2004, 18:2195-2224; Verstrepen L, Bekaert T, Chau TL, Tavernier J, Chariot A, Beyaert R. TLR-4, IL-1R and TNF-R signaling to NF-κB: variations on a common theme. Cell Mol Life Sci 2008, 65:2964-2978), and advances through computational modeling (Basak S, Behar M, Hoffmann A. Lessons from mathematically modeling the NF-κB pathway. Immunol Rev 2012, 246:221-238; Williams R, Timmis J, Qwarnstrom E. Computational models of the NF-KB signalling pathway. Computation 2014, 2:131), in this review we aim to summarize the current understanding of the NFκB signaling system itself, the molecular mechanisms, and systems properties that are key to its diverse biological functions, and we discuss remaining questions in the field. WIREs Syst Biol Med 2016, 8:227-241. doi: 10.1002/wsbm.1331 For further resources related to this article, please visit the WIREs website.
597 citations
TL;DR: The ‘mod‐form distribution’—the relative stoichiometries of each mod‐form—is introduced as the most informative measure of a protein's state as well as a quantitative framework in which to interpret ideas of ‘PTM codes’ that are emerging in several areas of biology.
Abstract: We discuss protein post-translational modification (PTM) from an information processing perspective. PTM at multiple sites on a protein creates a combinatorial explosion in the number of potential 'mod-forms', or global patterns of modification. Distinct mod-forms can elicit distinct downstream responses, so that the overall response depends partly on the effectiveness of a particular mod-form to elicit a response and partly on the stoichiometry of that mod-form in the molecular population. We introduce the 'mod-form distribution'-the relative stoichiometries of each mod-form-as the most informative measure of a protein's state. Distinct mod-form distributions may summarize information about distinct cellular and physiological conditions and allow downstream processes to interpret this information accordingly. Such information 'encoding' by PTMs may facilitate evolution by weakening the need to directly link upstream conditions to downstream responses. Mod-form distributions provide a quantitative framework in which to interpret ideas of 'PTM codes' that are emerging in several areas of biology, as we show by reviewing examples of ion channels, GPCRs, microtubules, and transcriptional co-regulators. We focus particularly on examples other than the well-known 'histone code', to emphasize the pervasive use of information encoding in molecular biology. Finally, we touch briefly on new methods for measuring mod-form distributions.
324 citations
TL;DR: Hybrid models allow for the integration of multiple interacting variables both intrinsically and extrinsically and are therefore perfectly suited to a systems biology approach to tumor growth.
Abstract: Cancer is a complex, multiscale process in which genetic mutations occurring at a subcellular level manifest themselves as functional changes at the cellular and tissue scale. The multiscale nature of cancer requires mathematical modeling approaches that can handle multiple intracellular and extracellular factors acting on different time and space scales. Hybrid models provide a way to integrate both discrete and continuous variables that are used to represent individual cells and concentrationordensityfields,respectively.Eachdiscretecellcanalsobeequipped with submodels that drive cell behavior in response to microenvironmental cues. Moreover, the individual cells can interact with one another to form and act as an integrated tissue. Hybrid models form part of a larger class of individualbased models that can naturally connect with tumor cell biology and allow for the integration of multiple interacting variables both intrinsically and extrinsically and are therefore perfectly suited to a systems biology approach to tumor
309 citations
TL;DR: The ability of agent‐based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggests that this modeling framework is well suited for translational systems biology.
Abstract: Agent-based modeling is an object-oriented, discrete event, population-focused method for the computational representation of dynamic systems. Agent-based models (ABMs) treat systems as aggregates of populations of interacting components governed by rules. This means of system representation allows ABMs to map well to how biological knowledge is represented and communicated. As a result, agent-based modeling is an intuitive means by which biomedical researchers can represent their knowledge in a dynamic computational form and in so doing can lower the threshold for the general biological researcher to engage in computational modeling. ABMs are particularly suited for representing the behavior of populations of cells (i.e., “cell-as-agents”) but have also been used to model lower level processes, such as molecular interactions when spatial and structural properties are involved, as well as higher level systems, such as in human populations in epidemiological studies. For purposes of its use in translational systems biology, we focus on the use of cell/tissue-as-agent ABMs and demonstrate how agent-based modeling can serve as an integrating framework for dynamic knowledge representation of biological systems.
283 citations