Eventos :: Cursos :: Introduction to multilayer networks Course

Títulos y resumen en todas partes
In the past two decades the analysis of mutualistic networks has advanced our understanding on the ecology, evolution and co-evolution of plants and pollinators. By moving beyond pairwise interactions, studies of mutualistic networks have revealed large variation in the degree of specialization, have emphasized the importance of particular species for the functioning of the entire mutualistic system and have linked the structure of networks to the stability and functioning of mutualistic systems. Nonetheless, most studies have used aggregated data, or have considered networks in “isolation”. In contrast, mutualistic systems are inherently multi-dimensional: they vary in space and time and often interact with non-mutualistic networks (e.g., plant-herbivore networks). Ecological multilayer networks are a new approach that aims to incorporate such dimensionality into the analysis by explicitly considering processes that operate across networks. As this framework is very new, and owing to the large possibilities in the definition of these networks, the analysis of these networks is not trivial. The purpose of this course is to introduce participants to this new framework and its methodology via hands-on analysis.
Fecha: 04/03/2020
Hora: 09 : 00
Duración: 1 Días 7 Horas 
Localización: Bizkaia Aretoa UPV/EHU: Abandoibarra Etorbidea 3, 48009 Bilbao
Contacto: Leyre Jiménez-Eguizábal
Teléfono: (34) 918997329
Coste: 70 € matrícula ordinaria / 50 € socios AEET y SIBECOL

Format:
 
The course will combine 1-2 short lectures, hands-on analysis and explanations on the board (as necessary). We will start with a short overview of ecological networks and an introduction to what are multilayer networks. We will then review the basic methodology for the analysis of multilayer networks, learn how to manipulate various kinds of multilayer data and get acquainted with multilayer analysis such as modularity. The analysis will be based on real data from mutualistic networks. The code I will give before the class will contain material for those who are less experienced as well as for more advanced participants.
 
 
Extras:
 
Participants are encouraged to bring their own data sets, which they can analyze instead of the example data. Depending on demand and time constraints, after the course we will try to set aside time to consult participants regarding their own data.
 
 
Pre-requisites:
 
Previous experience with R is necessary. Experience with network analysis is recommended but not obligatory. Participants will need to bring their own laptop with R and Rstudio pre-installed. For those who lack experience with network analysis in R it is recommendable to go through this tutorial beforehand: http://kateto.net/networks-r-igraph.   

Características del curso:
  • Coordinator: Ainhoa Magrach [ainhoa.magrach@bc3research.org]
  • Instructor: Shai Pilosof (Senior Lecturer (assistant professor) at Ben-Gurion University, Israel)
  • Venue: Bizkaia Aretoa UPV/EHU: Abandoibarra Etorbidea 3, 48009 Bilbao
  • Date: Wednesday, March 4th, 2020
  • Schedule: 9:00-13:00 & 15:00-18:00.
  • Price: AEET / SIBECOL members & UPV/EHU staff: 50 €; All other attendees: 70 €
  • Duration: 7 hours
  • Language: English
  • Maximum number of participants: 30
  • Registration deadline: January 30th, 2020

Organizer:



Collaborators: 
 

          
 
 
Pre-registration:
 
Quota of registration is already fulfilled.
 
Payment:
 
Payment can be made by bank transfer or bank deposit. Proof of payment with the participant´s name must be sent to info@aeet.org.
 
Payment data:
Entity name: Asociación Española de Ecología Terrestre
Address: Dpto. Biología y Geología, URJC. C/Tulipán s/n, 28933 Móstoles, Madrid, España.
CIF/VAT: G-50359017
Bank name: OpenBank
Account holder: Asociación Española de Ecología Terrestre
IBAN: ES70 0073 0100 5804 9730 5102
Cód. SWIFT / BIC: OPENESMM. 
 
For any other info please contact: info@aeet.org, tel.: +34 91 4887329 (de 9:00 a 14:00)
 
 
 
Mas sobre el tema: curso aeet; Multilayer networks

Actividades previstas