Coregulation mapping based on individual phenotypic variation in response to virus infection |
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Authors: | German Nudelman Yongchao Ge Jianzhong Hu Madhu Kumar Jeremy Seto Jamie L Duke Steven H Kleinstein Fernand Hayot Stuart C Sealfon James G Wetmur |
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Institution: | 1. Institute for Computing Applications 'M. Picone', National Research Council (CNR), Rome, Italy 2. Faculty of Pharmacy, University of Catania, Catania, Italy 3. IMGT, Laboratoire d'ImmunoGénétique Moléculaire, Institut de Génétique Humaine, UPR CNRS, 1142, Montpellier, France 4. Dipartimento di Ematologia e Scienze Oncologiche, Università di Bologna, Bologna, Italy
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Abstract: | Background Biology is moving fast toward the virtuous circle of other disciplines: from data to quantitative modeling and back to data. Models are usually developed by mathematicians, physicists, and computer scientists to translate qualitative or semi-quantitative biological knowledge into a quantitative approach. To eliminate semantic confusion between biology and other disciplines, it is necessary to have a list of the most important and frequently used concepts coherently defined. Results We propose a novel paradigm for generating new concepts for an ontology, starting from model rather than developing a database. We apply that approach to generate concepts for cell and molecule interaction starting from an agent based model. This effort provides a solid infrastructure that is useful to overcome the semantic ambiguities that arise between biologists and mathematicians, physicists, and computer scientists, when they interact in a multidisciplinary field. Conclusions This effort represents the first attempt at linking molecule ontology with cell ontology, in IMGT-ONTOLOGY, the well established ontology in immunogenetics and immunoinformatics, and a paradigm for life science biology. With the increasing use of models in biology and medicine, the need to link different levels, from molecules to cells to tissues and organs, is increasingly important. |
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