Dynamics of Mathematical Models in Biology ― Bringing Mathematics to Life

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 in cells. 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.

Mario R. Guarracino is a Staff Researcher at the National Research Council in the High Performance Computing and Networking Institute (ICAR-CNR). His research interests are in bioinformatics and high performance scientific computing; specifically machine learning, data mining algorithms, methods and software tools for biological data analysis, planning and development of high performance computational components for parallel and distributed problem solving environments.

Alessandra Rogato is a Researcher at the National Research Council in the Institute of Biosciences and Bioresources(ICAR-IBBR). Her research interests include molecular mechanisms underlying the ecological success of photosyntetic organisms and their capacity for handling different adaptative solutions in order to succeed in a variable environment.

Valeria Zazzuis a Researcher at the National Research Council in the Institute of Genetics and Biophysics(ICAR-IGB). Her research interests include quality control methodology, genome functional study, neural development and diseases.