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Special Issue "Multiscale and Hybrid Modeling of the Living Systems"
Deadline for manuscript submissions: closed (31 October 2016).
Ural Federal University, Head of Laboratory, Institute of Immunology and Physiology, Ural Branch of Russian Academy o Sciences, Pervomayskaya 106, 620049 Yekaterinburg, Russian Federation
Interests: mathematical physiology; biomechanics; cardiac computational models
Directeur de recherche au CNRS, Institut Camille Jordan, University Lyon 1, 69622 Villeurbanne, France
Interests: partial differential equations; mathematical modelling; population dynamics; biomedical modelling
Special Issues and Collections in MDPI journals
Special Issue in Computation: Pattern Formation in Population Dynamics
This Special Issue is intended to present recent advances and open problems in the development and computer implementation of high-resolution multi-parameter models, describing various levels of living systems organization. The relevant details of the experimental and mathematical techniques used for the quantitative characterization of the systems elements at different levels will be discussed.
Living systems are characterized by an enormous complexity of their structures, regulation, and dynamics. The mainstream approach to their analysis puts a strong emphasis on the acquisition of quantitative data and comprehensive measurements of a plethora of biological parameters. Nowadays it has become evident that, in order to gain a predictive understanding of the normal and pathological functioning of living systems, there is an urgent need of an efficient methodology for an information-rich, systems-based multiscale and hybrid modeling. The models which are developed to integrate a broad range of physical, chemical, biological phenomena with a large variation in their temporal and spatial scales represent a major challenge for numerical analysis and computational treatment. Advances in dynamic and global scale measurements of the system components at the gene-, cellular-, organ-, and whole organism-levels, and high resolution imaging technologies, should help to overcome the limitations of purely reductionist modeling approaches of the era preceding the development of systems biology. Our aim is to provide a comprehensive overview of the existing computational modeling approaches allowing one to include different scales into global models of living systems and enabling the identification of key targets to treat various diseases.
Prof. Dr. Gennady Bocharov
Prof. Dr. Olga Solovyova
Prof. Dr. Vitaly Volpert
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Computation is an international peer-reviewed open access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- Living Systems
- Integrative modeling
- Multiscale models
- Network models
- Hybrid models
- Systems Biology and Medicine
- Computational methods