Dynamics of Mathematical Models in Biology (PDF)
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This volume focuses on contributions from both the mathematics and life science community surrounding the concepts of time and dynamicity of nature, two significant elements which are often overlooked in modeling process to avoid exponential computations. The book is divided into three distinct parts: dynamics of genomes and genetic variation, dynamics of motifs, and dynamics of biological networks. Chapters included in dynamics of genomes and genetic variation analyze the molecular mechanisms and evolutionary processes that shape the structure and function of genomes and those that govern genome dynamics. The dynamics of motifs portion of the volume provides an overview of current methods for motif searching in DNA, RNA and proteins, a key process to discover emergent properties of cells, tissues, and organisms. The part devoted to the dynamics of biological networks covers networks aptly discusses networks in complex biological functions and activities that interpret processes incells. Moreover, chapters in this section examine several mathematical models and algorithms available for integration, analysis, and characterization.
Once life scientists began to produce experimental data at an unprecedented pace, it become clear that mathematical models were necessary to interpret data, to structure information with the aim to unveil biological mechanisms, discover results, and make predictions. The second annual "Bringing Maths to Life" workshop held in Naples, Italy October 2015, enabled a bi-directional flow of ideas from and international group of mathematicians and biologists. The venue allowed mathematicians to introduce novel algorithms, methods, and software that may be useful to model aspects of life science, and life scientists posed new challenges for mathematicians.
Valeria Zazzu - From 2013 until 2015, CNR Researcher at Institute of Genetics and Biophysics (IGB) "ABT" in Naples, Italy, involved in the project "New markers identifying dementia: a multidisciplinary approach", aiming at cross-linking dementia with neurodegenerative processes.From 2011 until 2012, member of the leading scientific coordination team for the IT Future of Medicine initiative, focussed on personalised medicine, one of the EU FET flagship pilot projects launched by the European Commission, at the Max Planck Institute for Molecular Genetics, Berlin, Germany.In 2011 PhD degree in Molecular Biology, Humboldt University, Berlin, Germany. Thesis title "The human G protein-coupled receptor GPR30: interaction
Mario Guarracino is researcher at High Performance Computing and Networking Institute of the Italian National Research Council. He received a PhD in Mathematics defending a thesis on projection techniques for parallel sparse linear algebra and an Ms in Applied Mathematics. His postdoctoral training from National Research Council focused on low cost high performance architectures for scientific computing. He has been collaborating with Center for Applied Optimization at University of Florida since 2005. He has taughtvarious undergraduate courses in both computer science and mathematics. His research interests include machine learning methods for computational biology and planning and development of high performance computational components for parallel and distributed problem solving environments. He is author of publications in the field of high performance scientific computing, computational biology and machine learning.
- 2016, 1st ed. 2016, 148 Seiten, Englisch
- Herausgegeben: Alessandra Rogato, Valeria Zazzu, Mario Guarracino
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3319457233
- ISBN-13: 9783319457239
- Erscheinungsdatum: 03.11.2016
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- Größe: 3.60 MB
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