CMM SCIENTIFIC SCHOOL

COMPUTATIONAL MOLECULAR MODELLING: 

PHYSICS- AND KNOWLEDGE -BASED METHODS AND VISUALIZATION FOR REAL LIFE APPLICATION

DUE TO THE SAS-COV-2 THE SCHOOL IS POSTPONED TO 2021

Due to the emergency created in all countries by the SAS-CoV-2 virus, and all the related organizational constraints and problems, 

the scientific committee decided to postpone the school to the next year, in the same period. 

This will hopefully allows to maintain the kind of useful interactions we had in mind while organizing the school.

We hope to have the confirmations of all the professor board and to receive the applications of the students that already applied. 

Thanks for your comprehension and See You Soon!

THE SCIENTIFIC SCHOOL

Computational molecular modeling (CMM) is worldwide recognized as an important area of science, with applications to a wide spectrum of disciplines, including biomedicine, nutraceuticals, functional foods, physics, chemistry and biochemistry, materials science, nanosciences, energy and environmental sciences.

CMM techniques have demonstrated in many years to be successful, leading to the development of computational models and to fast and accurate algorithms of increasing complexity.

These techniques are currently used by many researchers all over the world, both in the academic and industrial context, contributing to create innovative products and understanding complex mechanisms, overall contributing to improve life quality and impacting traditional animal tests.

TOPICS

For the second edition of the CMM school we propose a series of courses on “Physics- and Knowledge-based methods and Visualization for real life applications”.

The motivation for this choice is that today knowledge-based methods are rapidly expanding in the area of molecular modeling and their integration with physics-based ones is becoming more and more effective.

Databases containing information on molecules and biomolecules have been growing exponentially for over a decade and are today extremely redundant. Artificial intelligence, data mining, classification techniques allow to build models from the data themselves. Therefore these models, used to simulate the dynamics of molecules of interest, are obtained without the need to specify any underlying physical laws.


The main objectives of the school are:

  • to show the use of the CMM for comparison, integration and rationalisation of experimental data in real application cases;
  • to illustrate the possibilities offered by the new simulation techniques, and enable the students to independently, critically and consciously use specific packages apt for the computational problems of interest; 
  • to train experts in computational modeling able to support industrial and academical R&D labs, about experimental design, data interpretation and analysis and function driven discovery.

WHAT WILL YOU LEARN

Participants will be provided with the necessary tools to:

  •  understand what phenomena of interest may be studied with CMM techniques;
  • know what CMM techniques are available in various application areas and what are the theoretical basis of each methods;
  • analyze, interpret, compare the results of computational techniques for real applications;
  • understand the limits of applicability and the degree of reliability of the main classes of CMM techniques and be able to plan a virtual experiment in an optimal way and evaluate the reliability of the achieved results.

Finally, the school will provide students and researchers in the early stages with an important opportunity to interact with high-profile national and international scientists, and establish a network of contacts for eventual future collaborations.

FORMAT

The official language of the school is English.

The course is scheduled to begin on the morning of Monday July 27th; Mon-Fri will be full course days; the course will finish on Friday 31 in the afternoon.

The course is organized in a way to alternate lectures (typically in the morning) and parallel practical sessions (typically in the afternoon). The lectures will be public.

The practical sessions will give participants the opportunity to learn practical molecular modeling tools and test them in concrete cases. Access to the practical sessions is reserved to official School participants. 

Students will have ample time to meet and speak with lecturers, especially at the coffee breaks, lunches and the social event.

LECTURERS

Aatto Laaksonen, Stockholm University
Dario Estrin, Buenos Aires University
Amit Kumar, Cagliari University
Santiago Di Lella, Buenos Aires University
Francesca Mocci, Cagliari University
Maria Valentini, CRS4
Enrico Pieroni, CRS4
Giancarlo Cappellini, Cagliari University
Roberto Cardia, Cagliari University
Claudio Melis, Cagliari University
Vincenzo Martorana, CNR Palermo
Francesco Sciortino, Rome La Sapienza University
Francesca Spyrakis, Torino University
Leon De Villiers Engelbrecht, Cagliari University

Leif Eriksson, Gothenburg University

Lecture Constanze Kalcher, OVITO GmbH i Gr.

“The school is organized thanks to the economic and organizing support of the regional agency Sardegna Ricerche and the Autonomous  Region of Sardinia, through the scientific School 2020 funding.”


cmm@crs4.it

+39 070 92501

CRS4, Building 2, Technology Park of Sardinia, Pula - Italy

Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.