Course Overview: Most high-throughput bioinformatics work these days takes place on the Linux command line. The programs which do the majority of the computational heavy lifting — genome assemblers, read mappers, and annotation tools — are designed to work best when used with a command-line interface. Because the command line can be an intimidating environment, many biologists learn the bare minimum needed to get their analysis tools working. This means that they miss out on the power of Linux to…

Course Overview: The term ‘landscape genetics’ has been applied studies that integrate ecological context and intervening landscape into population genetic analyses of contemporary processes such as gene flow and migration.  This course will cover the basics of both quantitative landscape ecology and population genetics, focusing on how we develop and evaluate spatial/genetic analyses using the R platform. Intended Audience This course is suitable for graduate students, postdoctoral researchers, and primary investigators interested in learning how to integrate landscape ecological and…

Course Overview: This application-driven course will provide a founding in the basic theory & practice of Bayesian statistics, with a focus on MCMC modeling for ecological & epidemiological problems. Starting from a refresher on probability & likelihood, the course will take students all the way to cutting-edge applications such as state-space population modelling & spatial point-process modelling. By the end of the week, you should have a basic understanding of how common MCMC samplers work and how to program them,…

Course Overview: Python is a dynamic, readable language that is a popular platform for all types of bioinformatics work, from simple one-off scripts to large, complex software projects. It gives an overview of the language with an emphasis on practical problem-solving, using examples and exercises drawn from various aspects of bioinformatics work. After completing the workshop, students should be in a position to (1) apply the skills they have learned to tackle problems in their own research and (2) continue…

Course Overview: The course will deal with different aspects related to the use of remote sensing and GIS in spatial ecology by using the Free and Open Source Software GRASS GIS coupled with R. By the end of this 5-day practical course, attendees will have the capacity to deal with ecological patterns and processes by using GIS and remote sensing algorithms. The increasing availability of open ecological and geographical data through networks such as the Global Biodiversity Information Facility (GBIF,…

Course Overview: This course will provide an introduction to working with real-life data typical of those encountered in the field of evolutionary biology and ecology. The course will be delivered by Dr. Luc Bussiere, Dr. Tom Houslay and Dr. Ane Timenes Laugen who are all practicing academics in the field of evolutionary biology.  This five day course will consist of series of modules (each lasting roughly half a day) covering model selection and simplification, generalised linear models, mixed effects models,  and non-linear models. Along…

Course Overview: The main objectives of the course are to teach the theoretical bases of phylogenetic analysis, and to give the ability to initiate a phylogenetic analysis starting from the files of molecular sequences until the interpretation of the results and the graphics. The introduction will cover a brief historical background and an overview of the different methods of phylogenetic inference. Different kinds of data will be considered, but with a special emphasis on DNA sequences. The software used will…

Course Overview: This course will cover introductory hierarchical modelling for real-world data sets from a Bayesian perspective. These methods lie at the forefront of statistics research and are a vital tool in the scientist’s toolbox. The course focuses on introducing concepts and demonstrating good practice in hierarchical models. All methods are demonstrated with data sets which participants can run themselves. Participants will be taught how to fit hierarchical models using the Bayesian modelling software Jags and Stan through the R…

Course Overview: The course will describe different aspects and methods of functional ecology, from organisms to ecosystems, combining theoretical lessons with hands-on real data. Lectures will cover general aspects of functional ecology, including definitions, measurements and different applications of functional traits. They will include analysis of traits at organismal, community and ecosystem levels, including relationships to ecosystem function and ecological services, and use examples from land use change, climate change, and multi-trophic interactions. An overview of existing computational methods, including…

Course Overview: To follow Intended Audience To follow Venue - SCENE - Google Map - Directions Availability - 20 places Duration – 5 days Contact hours – Approx. 35 hours ECT’s – Equal to 3 ECT’s Language - English Packages We offer COURSE ONLY and ACCOMMODATION PACKAGES; • COURSE ONLY – Includes lunch and refreshments. • ACCOMMODATION PACKAGE (to be purchased in addition to the course only option) – Includes breakfast, lunch, dinner, refreshments, minibus to and from meeting point and accommodation. Accommodation…

Course Overview: To follow Intended Audience Research postgraduates, practicing academics and primary investigators in spatial ecology and management and environmental professionals in government and industry. Venue - SCENE - Google Map - Directions *Please note that Millport Field Station is very easy to reach using public transport. Availability - 36 places Duration – 5 days Contact hours – Approx. 37 hours ECT’s – Equal to 3 ECT’s Language - English Packages We offer COURSE ONLY and ACCOMMODATION PACKAGES; • COURSE ONLY –…

Course Overview: This course will provide an introduction to modern multivariate techniques, with a special focus on the analysis of abundance or presence/absence data. Multivariate analysis in ecology has been changing rapidly in recent years, with a focus now on formulating a statistical model to capture key properties of the observed data, rather than transformation of data using a dissimilarity-based framework. In recent years, model-based techniques have been developed for hypothesis testing, identifying indicator species, ordination, clustering, predictive modelling, and…