The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Exploring Structural and Dynamical Properties Microtubules by Means of Artificial Neural Networks
|
|
Author(s): R. Pizzi (Università degli Studi di Milano, Italy), S. Fiorentini (Università degli Studi di Milano, Italy), G. Strini (Università degli Studi di Milano, Italy)and M. Pregnolato (Università degli Studi di Pavia, Italy)
Copyright: 2013
Pages: 14
Source title:
Complexity Science, Living Systems, and Reflexing Interfaces: New Models and Perspectives
Source Author(s)/Editor(s): Franco Orsucci (University College London, UK & Institute for Complexity Studies, Italy)and Nicoletta Sala (University of Lugano, Switzerland)
DOI: 10.4018/978-1-4666-2077-3.ch005
Purchase
|
Abstract
Microtubules (MTs) are cylindrical polymers of the tubulin dimer, are constituents of all eukaryotic cells cytoskeleton and are involved in key cellular functions and are claimed to be involved as sub-cellular information or quantum information communication systems. The authors evaluated some biophysical properties of MTs by means of specific physical measures of resonance and birefringence in presence of electromagnetic field, on the assumption that when tubulin and MTs show different biophysical behaviours, this should be due to their special structural properties. Actually, MTs are the closest biological equivalent to the well-known carbon nanotubes (CNTs), whose interesting biophysical and quantum properties are due to their peculiar microscopic structure. The experimental results highlighted a physical behaviour of MTs in comparison with tubulin. The dynamic simulation of MT and tubulin subjected to electromagnetic field was performed via MD tools. Their level of self-organization was evaluated using artificial neural networks, which resulted to be an effective method to gather the dynamical behaviour of cellular and non-cellular structures and to compare their physical properties.
Related Content
|
David Zelinka, Bassel Daher.
© 2021.
30 pages.
|
|
David Zelinka, Bassel Daher.
© 2021.
29 pages.
|
|
Narendranath Shanbhag, Eric Pardede.
© 2021.
31 pages.
|
|
Marc Haddad, Rami Otayek.
© 2021.
20 pages.
|
|
Reem A. ElHarakany, Alfredo Moscardini, Nermine M. Khalifa, Marwa M. Abd Elghany, Mona M. Abd Elghany.
© 2021.
23 pages.
|
|
Sanjay Soni, Basant Kumar Chourasia.
© 2021.
35 pages.
|
|
Lina Carvajal-Prieto, Milton M. Herrera.
© 2021.
20 pages.
|
|
|