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Toward Rigorous Comprehension of Biological Complexity: Modeling, Execution, and Visualization of Thymic T-Cell Maturation
Author(s) -
Sol Efroni,
David Harel,
Irun R. Cohen
Publication year - 2003
Publication title -
genome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.556
H-Index - 297
eISSN - 1549-5469
pISSN - 1088-9051
DOI - 10.1101/gr.1215303
Subject(s) - executable , biology , set (abstract data type) , interface (matter) , visualization , data set , computer science , computational biology , programming language , data mining , artificial intelligence , pulmonary surfactant , biochemistry , gibbs isotherm
One of the problems biologists face is a data set too large to comprehend in full. Experimenters generate data at an ever-growing pace, each from their own niche of interest. Current theories are each able, at best, to capture and model only a small part of the data. We aim to develop a general approach to modeling that will help broaden biological understanding. T-cell maturation in the thymus is a telling example of the accumulation of experimental data into a large disconnected data set. The thymus is responsible for the maturation of stem cells into mature T cells, and its complexity divides research into different fields, for example, cell migration, cell differentiation, histology, electron microscopy, biochemistry, molecular biology, and more. Each field forms its own viewpoint and its own set of data. In this study we present the results of a comprehensive integration of large parts of this data set. The integration is performed in a two-tiered visual manner. First, we use the visual language of Statecharts, which makes specification precise, legible, and executable on computers. We then set up a moving graphical interface that dynamically animates the cells, their receptors, the different gradients, and the interactions that constitute thymic maturation. This interface also provides a means for interacting with the simulation.

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