Systems Immunology: An Introduction To Modeling...
The need to write code can pose a significant barrier for individuals who do not have prior coding experience. To reduce this barrier, I wrote software that allows individuals to obtain an introduction to simulation modeling of within-host infection and immune dynamics, without the need to read or write computer code. The software, called Dynamical Systems Approach to Immune Response Modeling (DSAIRM), is implemented as a freely available package for the widely used R programming language. The DSAIRM package is meant for immunologists and other bench scientists who have little or no coding and modeling experience and who are interested in learning how to use systems simulation models to study within-host infection and immune response dynamics.
Systems Immunology: An Introduction to Modeling...
Organoids are in vitro representations of an organ or tissue that recapitulate the functional and structural features of the originating organ [129, 130]. Organoid culture has been used to model complex human and murine tissues, including lung, intestine, and brain [130, 131]. The use of the term 'organoid' varies substantially by field; although in many instances they are derived from an originating stem cell population, the consistent features of different organoid systems are relevant tissue patterning and retention of in vivo function. The organoid field has made significant advancements in modeling non-immune organs from mice and humans. Several groups have expanded organoid culture into immune tissues from mice that successfully support humoral responses [132,133,134,135,136,137,138]. Ankur Singh and colleagues extended organoid systems to immune tissues in a fully animal-independent way [132, 133]. Using an elegant murine cell-based system, they captured the essence of an immune microenvironment in vitro that permits B cell differentiation, promotes germinal center development, and supports antibody production [132, 133]. Although some facets of organoid culture are currently impractical to translate to a fully human system (dependence on exogenous protein expression from cell lines, re-introduction into living hosts), such methods have great potential to model immune processes. Our group has recently created human immune organoids from primary tonsil tissues that permit in vitro analysis of antigen-specific T and B cell responses. The system we have developed seeks to translate the existing excellent murine organoid models to humans and to allow more mechanistic immune studies to be performed on human tissues.
Neuroblastoma is the first human condition that has been investigated from a systems level perspective in recent years [19]. Logan et al. constructed a regulatory network model for the main oncogene in neuroblastoma, MYCN, and consequently evaluated the perturbation of this model through the introduction of retinoid drugs (fenretinide, 13-cis-retinoic acid), therefore allowing enhanced insight into the responses of NB tumours to retinoid therapy through the identification of novel molecular interaction hypotheses that can be put to the test in a laboratory setting [19].
This book is an introduction to the language of systems biology, which is spoken among many disciplines, from biology to engineering. Authors Thomas Sauter and Marco Albrecht draw on a multidisciplinary background and evidence-based learning to facilitate the understanding of biochemical networks, metabolic modeling and system dynamics. Their pedagogic approach briefly highlights core ideas of concepts in a broader interdisciplinary framework to guide a more effective deep dive thereafter. The learning journey starts with the purity of mathematical concepts, reveals its power to connect biological entities in structure and time, and finally introduces physics concepts to tightly align abstraction with reality. This workbook is all about self-paced learning, supports the flipped-classroom concept, and kick-starts with scientific evidence on studying. Each chapter comes with links to external YouTube videos, learning checklists, and Integrated real-world examples to gain confidence in thinking across scientific perspectives. The result is an integrated approach that opens a line of communication between theory and application, enabling readers to actively learn as they read. This overview of capturing and analyzing the behavior of biological systems will interest adherers of systems biology and network analysis, as well as related fields such as bioinformatics, biology, cybernetics, and data science.
This book provides an introduction to genetic concepts such as reproductive systems, recombination, mutation, segregation and linkage analysis, inbreeding, quantitative inheritance, fertility regulation, population genetics and polyploidy. 041b061a72