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DTSTART;VALUE=DATE:20260112
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UID:10000541-1768176000-1768607999@prstats.org
SUMMARY:Introduction to Generalised Linear Models using R (GLMG01)
DESCRIPTION:Joint Species Distribution Modelling (JSDM) using HMSC: A Hierarchical Modelling Approach (JSDM01)\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Event Date \nMonday\, December 1st\, 2025\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n					\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Course Format\nThis is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link\, a good internet connection is essential. \nTime Zone\nTIME ZONE – Portugal (GMT+1) local time – however all sessions will be recorded and made available allowing attendees from different time zones to follow. \nPlease email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you). \n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				About This Course\n				Have you built an Ecological Niche Model? If yes\, you have already encountered challenges on data preparation\, or have struggled with issues in models fitting and accuracy. This course will teach you how to overcome these challenges and improve the accuracy of your ecological niche models. By the end of 5-day practical course\, you will have the capacity to filter records and select your variables with variance inflation factor; to test effect of Maxent regularization parameter in models performance; to validate models performance and accuracy; to perform MESS analysis\, null models\, and mechanistic models\, as well as to build your “virtual species”. \nEcological niche\, species distribution\, habitat distribution\, or climatic envelope models are different names for mechanistic and correlative models\, which are empirical or mathematical approaches to the ecological niche of a species. These methods relate different types of ecogeographical variables (environmental\, topographical\, human) to species physiological data or geographical locations\, in order to identify the factors limiting and defining the species&#39; niche. ENMs have become popular because of their efficiency in the design and implementation of conservation management. \nBy the end of 5-day practical course should be able to: \n\nfilter records and select your variables with variance inflation factor;\ntest the effect of Maxent regularization parameter in models performance;\nvalidate models performance and accuracy;\nperform MESS analysis\, null models\, and mechanistic models\, as well as to build your “virtual species”.\n\nStudents will learn to use functions implemented in the packages “usdm”; “dismo”; “ENMEval”; “SDMvspecies”; “spThin”; and “NicheMapper” among others. \n			\n				\n				\n				\n				\n				Intended Audiences\n				This course is orientated to PhD and MSc students\, as well as other students and researchers working on biogeography\, spatial ecology\, or related disciplines\, with experience in ecological niche models. \n			\n				\n				\n				\n				\n				Venue\n				Delivered remotely\n			\n				\n				\n				\n				\n				Course Details\n				Time Zone – Portugal (GMT+!) local time \nAvailability – 24 places \nDuration – 5 days\, 7 hours a day \nContact hours – Approx. 35 hours \nECT’s – Equal to 3ECT’s \nLanguage – English \n			\n				\n				\n				\n				\n				Teaching Format\n				The course will be mainly practical\, with some theoretical lectures. All modelling processes and calculations will be performed with R\, the free software environment for statistical computing and graphics (http://www.r-project.org/). Students will learn to use functions implemented in the packages “usdm”; “dismo”; “ENMEval”; “SDMvspecies”; “spThin”; and “NicheMapper” among others. \n			\n				\n				\n				\n				\n				Assumed quantitative knowledge\n				A basic understanding of ecological niche models and biogeography in general is required\, thus we will assume the attendees know how to run an ecological niche model. \n			\n				\n				\n				\n				\n				Assumed computer background\n				Solid knowledge in Geographical Information Systems and R statistical package is necessary. It is also essential to have experience in ecological niche models. We will focus exclusively on advanced methods. If you need an introductory course on ecological niche models\, please consider attending our basic course on PRStatistics (www.prstats.org). \n			\n				\n				\n				\n				\n				Equipment and software requirements\n				\nA laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs\, Macs\, and Linux computers. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/. \n\n\nAll the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed\, and a full list of required packages will be made available to all attendees prior to the course. \n\n\nA working webcam is desirable for enhanced interactivity during the live sessions\, we encourage attendees to keep their cameras on during live zoom sessions. \n\n\nAlthough not strictly required\, using a large monitor or preferably even a second monitor will improve he learning experience \n\n\nDownload R \n\n\nDownload RStudio \n\n\nDownload Zoom \n\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n	\n		Tickets	\n	\n	\n	\n	\n	\n	\n		The numbers below include tickets for this event already in your cart. Clicking "Get Tickets" will allow you to edit any existing attendee information as well as change ticket quantities.	\n\n\n\n	\n	\n		HMSC01 ONLINE\n	\n	HMSC01 ONLINE\n\n	\n		\n		\n				\n					£\n					450.00\n				\n						\n\n			\n			Unlimited	\n				\n			\n				Open the ticket description.\n				More			\n			\n				Close the ticket description.\n				Less			\n	\n	\n\n			\n			\n	Decrease ticket quantity for HMSC01 ONLINE\n	-\n		\n	\n		Quantity	\n	\n\n		\n	Increase ticket quantity for HMSC01 ONLINE\n	+\n		\n	\n				\n		\n\n		\n	\n		Quantity:	\n	0\n\n	\n	\n		Total:	\n	\n		\n				\n					£\n					0.00\n				\n				\n\n			\n	Get Tickets\n	\n\n	\n		\n	\n\n		\n	\n\n		\n	\n\n	\n\n\n\n\n\n	\n\n\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				PLEASE READ – CANCELLATION POLICY \nCancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered\, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.\n			\n				\n				\n				\n				\n				\nIf you are unsure about course suitability\, please get in touch by email to find out more oliverhooker@prstatistics.com \n\n			\n			\n				\n				\n				\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				COURSE PROGRAMME\n  \n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Monday 1st\n				Day 1 – Classes from 09:30 to 17:30 \n\nENM guide: how to model\nENM R packages.\nSources of environmental variables using geodata package.\nGetting species records with geodata package.\n\n			\n				\n				\n				\n				\n				Tuesday 2nd\n				Day 2 – Classes from 09:30 to 17:30 \n\nVariable selection with variance inflation factor (VIF) and usdm packages.\nChoosing the correct study area.\nFiltering records using usdm/spThin packages.\nChoosing pseudo-absences with Biomod2 package.\n\n			\n				\n				\n				\n				\n				Wednesday 3rd\n				Day 3 – Classes from 09:30 to 17:30 \n\nSplit records in training and test with ENMeval package.\nTest effect of Maxent regularization parameter.<.li>\nComparing correlative models with AIC\, with ENMeval package.\n\n			\n				\n				\n				\n				\n				Thursday 4th\n				Day 4 – Classes from 09:30 to 17:30 \n\nMESS practice with Biomod2 package.\nValidate models null models.\nVirtualSpecies virtualspecies packages.\n\n			\n				\n				\n				\n				\n				Friday 5th\n				Day 5 – Classes from 09:30 to 17:30 \n\nMechanistic model NicheMapper packages.\n\n			\n			\n				\n				\n				\n				\n				\n				\n					Dr. Neftali Sillero\n					\n					Neftalí Sillero works in the analysis and identification of biodiversity spatial patterns\, from species to populations and individuals. For this\, he uses four powerful tools to better understand how space influence biodiversity: Geographical Information Systems\, Remote Sensing\, Ecological Niche Modelling\, and Spatial Statistics. His main areas of research are: application of new technologies on species’ distributions atlases\, ecological modelling of species’ ranges\, identification of biogeographical regions and species’ chorotypes\, mapping and modelling road-kill hotspots\, and spatial analyses of home ranges. \nHe has more than 10 years’ experience working in ecological niche models. He has authored >70 peer reviewed publications and he is since 2007 Chairman of the Mapping Committee of the Societas Herpetologica Europaea\, where he is the PI of the NA2RE project (www.na2re.ismai.pt)\, the New Atlas of Amphibians and Reptiles of Europe \nPersonal website \nWork Webpage \nResearchGate \nGoogleScholar \n					\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Teaches\n				\nEcological Niche Modelling Using R (ENMR)\nAdvanced Ecological Niche Modelling Using R (ANMR)\nGIS And Remote Sensing Analyses With R (GARM)\n\n			\n				\n				\n				\n				\n				Teaches\n				\nEcological Niche Modelling Using R (ENMR)\nAdvanced Ecological Niche Modelling Using R (ANMR)\nGIS And Remote Sensing Analyses With R (GARM)\n\n			\n			\n				\n				\n				\n				\n				\n				\n					Dr. Salvador Arenas-Castro\n					\n					Dr. Salvador Arenas-Castro is a broad-spectrum ecologist with interesting in differentintegrative perspective of the fundamental ecology\, macroecology and biogeographywith their both application and relationship to climate and land management. He is alsoexploring other research sources in agroecology\, forestry\, spatial ecology\, andecoinformatics\, all addressed by explicitly considering the spatial component ofecological processes\, mainly applying spatially explicit modelling approaches\, GIS andremote sensing techniques. Please check his webpage for further information:https://salvadorarenascastro.wordpress.com \nGoogle Scholar: https://scholar.google.com/citations?user=UAYiB5UAAAAJ&hl=es&oi=aoResearchGate: https://www.researchgate.net/profile/Salvador-Arenas-Castro
URL:https://prstats.org/course/introduction-to-generalised-linear-models-using-r-glmg01/
LOCATION:Delivered remotely (United Kingdom)\, Western European Time Zone\, United Kingdom
CATEGORIES:Home Courses,Live Online Courses
ATTACH;FMTTYPE=image/jpeg:https://prstats.org/wp-content/uploads/2025/09/GLMG01.jpg
GEO:53.1423672;-7.6920536
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DTSTART;VALUE=DATE:20260126
DTEND;VALUE=DATE:20260130
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CREATED:20250424T121623Z
LAST-MODIFIED:20260408T105556Z
UID:10000477-1769385600-1769731199@prstats.org
SUMMARY:Introduction to Python for Ecologists and Evolutionary Biologists (IPYB01)
DESCRIPTION:Joint Species Distribution Modelling (JSDM) using HMSC: A Hierarchical Modelling Approach (JSDM01)\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Event Date \nTuesday\, 16th September\, 2025\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n					\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Course Format\nThis is a ‘LIVE COURSE’ – the instructors will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link\, a good internet connection is essential. \nCOURSE PROGRAM\n\nTIME ZONE – UK (GMT+1) local time – however all sessions will be recorded and made available allowing attendees from different time zones to follow. \n\n\nPlease email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you. \n\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				About This Course\n				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. This workshop aims to give novice programmers an introduction to using Python for research in evolutionary biology and genomics by using biological examples throughout. We will use example datasets and problems themed around sequence analysis\, taxonomy and ecology\, with plenty of time for participants to work on their own research data. \nThis workshop is aimed at complete beginners and assumes no prior programming experience. 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. \nAfter completing the workshop\, students should be able to: \n\nApply the skills they have learned to tackling problems in their own research\nContinue their Python education in a self-directed way. All course materials (including copies of presentations\, practical exercises\, data files\, and example scripts prepared by the instructing team) will be provided electronically to participants.\n\n			\n				\n				\n				\n				\n				Intended Audiences\n				This workshop is aimed at all researchers and technical workers with a background in biology who want to learn programming. The syllabus has been planned with complete beginners in mind; people with previous programming experience are welcome to attend as a refresher but may find the pace a bit slow. If in doubt\, take a look at the detailed session content below or drop Martin Jones (martin@pythonforbiologists.com) an email. \nStudents should have enough biological background to appreciate the examples and exercise problems (i.e. they should know about DNA and protein sequences\, what translation is\, and what introns and exons are). No previous programming experience or computer skills (beyond the ability to use a text editor) are necessary\, but you’ll need to have a laptop with Python installed. \n			\n				\n				\n				\n				\n				Venue\n				Delivered remotely \n			\n				\n				\n				\n				\n				Course Details\n				Time zone – UK (GMT+1) local time \nAvailability – 20 \nDuration – 4 days\, 8 hours per day \nContact hours – Approx. 28 hours \nECT’s – Equal to 3 ECT’s \nLanguage – English \n			\n				\n				\n				\n				\n				Teaching Format\n				Lectures/discussions of Python code\, libraries and techniques delivered using interactive notebooks. Workshop/practical time for students to tackle carefully designed programming challenges that use the material from the discussion sessions. Usually followed up by discussion of solutions\, wrap up and summarisation. \n			\n				\n				\n				\n				\n				Assumed quantative knowledge\n				Little technical knowledge is assumed – we will be focussing more on applied problem-solving and less on statistics\, mathematics and interpretation. No maths is involved beyond basic addition/subtraction/powers etc. \n			\n				\n				\n				\n				\n				Assumed computer background\n				This course is suitable for complete beginners; all that is necessary is admin rights on a laptop in order to be able to install software. Pre course instructions will contain links to all software and data files that are necessary. \n			\n				\n				\n				\n				\n				Equipment and software requirements\n				\nA laptop computer with a working version of Python is required. Python is free and open-source software for PCs\, Macs\, and Linux computers.\n \nParticipants should be able to install additional software on their computers during the course (please ensure you have administration rights to your computer).\n\nAlthough not absolutely necessary\, a large monitor and a second screen could improve the learning experience. Participants are also encouraged to keep their webcams active to increase their interaction with the instructor and other students. \nDownload Python \n  \n\n\n  \n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n	\n		Tickets	\n	\n	\n	\n	\n	\n	\n		The numbers below include tickets for this event already in your cart. Clicking "Get Tickets" will allow you to edit any existing attendee information as well as change ticket quantities.	\n\n\n\n	\n	\n		HMSC01 ONLINE\n	\n	HMSC01 ONLINE\n\n	\n		\n		\n				\n					£\n					450.00\n				\n						\n\n			\n			Unlimited	\n				\n			\n				Open the ticket description.\n				More			\n			\n				Close the ticket description.\n				Less			\n	\n	\n\n			\n			\n	Decrease ticket quantity for HMSC01 ONLINE\n	-\n		\n	\n		Quantity	\n	\n\n		\n	Increase ticket quantity for HMSC01 ONLINE\n	+\n		\n	\n				\n		\n\n		\n	\n		Quantity:	\n	0\n\n	\n	\n		Total:	\n	\n		\n				\n					£\n					0.00\n				\n				\n\n			\n	Get Tickets\n	\n\n	\n		\n	\n\n		\n	\n\n		\n	\n\n	\n\n\n\n\n\n	\n\n\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\nPLEASE READ – CANCELLATION POLICY \n\n\nCancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered\, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited \n\n			\n				\n				\n				\n				\n				\nIf you are unsure about course suitability\, please get in touch by email to find out more oliverhooker@prstatistics.com \n\n \n			\n			\n				\n				\n				\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				COURSE PROGRAMME\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Tuesday 16th\n				Day 1  – Classes form 09:30 – 17:30 \nSession 1 : Introduction\, environment and text manipulation \n\nIn this session I introduce the students to Python and explain what we expect them to get out of it and how learning to program can benefit their research. I explain the format of the course and take care of any housekeeping details (like coffee breaks and catering arrangements). I outline the edit-run-fix cycle of software development and talk about how to avoid common text editing errors. In this session\, we also check that the computing infrastructure for the rest of the course is in place (e.g. making sure that everybody has an appropriate version of Python installed). Next\, students learn to write very simple programs that produce output to the terminal\, and in doing so become comfortable with editing and running Python code. This session also introduces many of the technical terms that we’ll rely on in future sessions. I run through some examples of tools for working with text and show how they work in the context of biological sequence manipulation. We also cover different types of errors and error messages\, and learn how to go about fixing them methodically. Core concepts introduced: terminals\, standard output\, variables and naming\, strings and characters\, special characters\, output formatting\, statements\, functions\, methods\, arguments\, comments.\n\nSession 2 : Files\, slices and user interfaces \n\nI introduce this session by talking about the importance of files in bioinformatics pipelines and workflows\, and we then explore the Python interfaces for reading from and writing to files. This involves introducing the idea of types and objects\, and a bit of discussion about how Python interacts with the operating system. We will also take a look at Python’s slice syntax\, which will play an important role later in the course once we introduce data structures. The practical session is spent combining the techniques from the first session with the file IO tools to create basic file processing scripts. Core concepts introduced: objects and classes\, paths and folders\, relationships between variables and values\, text and binary files\, newlines.\n\n			\n				\n				\n				\n				\n				Wednesday 17th\n				Day 2  – Classes form 09:30 – 17:30 \nSession 3 : Lists and loops \n\nIn this session we’ll start by thinking about the kinds of programs that we need to write for our research work. An important idea is that we want to write programs that can deal with arbitrary amounts of data. In order to do so\, we need two things: a way of *storing* large collections of values\, and a way of *processing* them. In Python\, **lists** and **loops** do these jobs respectively. We’ll go over the new syntax needed for each\, and see how together they allow us to write programs that are much closer to being useful in the real world. This new syntax will allow us to see how lists\, strings and files all share similar behaviour and how we can take advantage of that fact to write concise code. In the practical session we’ll tackle some problems that involve larger data files. Core concepts introduced: lists and arrays\, blocks and indentation\, variable scoping\, iteration and the iteration interface\, ranges.\n\nSession 4 : conditions and flow control \n\nWe will start this session by using the idea of decision making as a way to introduce conditional tests\, and outline the different building blocks of conditions before showing how conditions can be combined in an expressive way. We look at the different ways that we can use conditions to control program flow\, and how we can structure conditions to keep programs readable. These simple ideas combine with the material we have already covered to allow us to write programs that can follow rules and enforce logic. Correspondingly\, in the practical session we’ll be able to attempt some complex filtering challenges on a structured CSV file. Core concepts introduced: Truth and falsehood\, Boolean logic\, identity and equality\, evaluation of statements\, branching.\n\n			\n				\n				\n				\n				\n				Thursday 18th\n				Day 3 – Classes from 09:30 – 17:30 \nSession 5 : Organizing and structuring code \n\nWe’ll start off by discussing functions that we’d like to see in Python before considering how we can add to our computational toolbox by creating our own. We examine the nuts and bolts of writing functions before looking at best practice ways of making them usable. We also look at a couple of advanced features of Python – named arguments and defaults. This session ends with a first look at the concepts behind automated testing\, and the easiest way to get started with tests in Python. The practical session makes extensive use of automated testing\, with students writing functions to pass a series of unit tests. Core concepts introduced: argument passing\, encapsulation\, data flow through a program\, unit testing.\n\nSession 6 : The Python standard library and Regular expressions \n\nWe begin this sesion by browsing the documentation for the Python standard library and discussing how it fits in with the core parts of Python that we’ve already discussed\, along with other libraries of code that students may have already encountered. To explore how Python’s module system works in detail we will take a close look at one particular module: the one that deals with regular expressions. We’ll see how a range of common problems in bioinformatics can be described in terms of pattern matching\, and give an overview of Python’s regex tools. We look at the building blocks of regular expressions themselves\, and learn how they are a general solution to the problem of describing patterns in strings\, before practising writing some specific examples of regular expressions. Core concepts introduced: domain-specific languages\, modules and namespaces.\n\n			\n				\n				\n				\n				\n				Friday 19th\n				Day 4 – Classes form  09:30 – 17:30 \nSession 7 : Dictionaries \nAll of the data sets that we’ve considered so far in the course fit nicely into the list paradigm. In this session\, it’s time to introduce the second major data structure offered by Python: the dictionary. To do this\, we’ll look at a classic bioinformatics problem – kmer counting – and see how lists aren’t a good fit before learning the new syntax that we need to make dictionaries. Comparing the list and dictionary solutions will make it clear when we should use each approach. We’ll wrap up by discussing a few more examples of key-value data and see how the problem of storing them is a common one across bioinformatics and programming in general. In the practical session we will practice writing programs that create dictionaries\, and ones that use dictionaries\, including another classic bioinformatics problem: DNA to protein translation. Core concepts introduced: paired data types\, hashing\, key uniqueness\, argument unpacking and tuples. \nSession 8 : File management and housekeeping scripts \nThis session concerns a part of the Python standard library that is boring but useful – the modules concerned with file manipulation. We will cover the tools that Python gives us to automate the common repetitive housekeeping operations that are part of many bioinformatics projects\, but rarely make it into the final publication – things like renaming\, moving and deleting files\, creating folders\, etc. The notebook part of this session is quite brief\, giving us a generous amount of practical time to tackle an example of a bioinformatics data pre-processing problem: organizing a collection of DNA sequences by length. Although the problem can be stated very concisely\, we’ll quickly see that there are quite a few subtleties to it\, giving us a chance to think about program state of multiple runs\, processing multiple files\, and creating multiple output files. \n\n			\n			\n				\n				\n				\n				\n				\n				\n					Dr. Martin Jones\n					\n					Martin a freelance trainer specialising in teaching programming (mostly Python) and Linux skills to researchers in the field of biology. He trained as a biologist and completed his PhD in large-scale phylogenetics in 2007\, then held a number of academic positions at the University of Edinburgh ending in a two year stint as Lecturer in Bioinformatics. I launched Python for Biologists in 2015 and have been teaching and writing full-time ever since.
URL:https://prstats.org/course/introduction-to-python-for-biologists-ipyb01/
LOCATION:Delivered remotely (United Kingdom)\, Western European Time Zone\, United Kingdom
CATEGORIES:All Live Courses,Home Courses,Live Online Courses
ATTACH;FMTTYPE=image/jpeg:https://prstats.org/wp-content/uploads/2025/04/IPYB01.jpg
GEO:53.1423672;-7.6920536
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260126
DTEND;VALUE=DATE:20260130
DTSTAMP:20260419T111206
CREATED:20250918T143835Z
LAST-MODIFIED:20260408T130034Z
UID:10000537-1769385600-1769731199@prstats.org
SUMMARY:RNA-Seq Analysis (RNAA01)
DESCRIPTION:Joint Species Distribution Modelling (JSDM) using HMSC: A Hierarchical Modelling Approach (JSDM01)\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Event Date \nMonday\, December 1st\, 2025\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n					\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Course Format\nThis is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link\, a good internet connection is essential. \nTime Zone\nTIME ZONE – Portugal (GMT+1) local time – however all sessions will be recorded and made available allowing attendees from different time zones to follow. \nPlease email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you). \n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				About This Course\n				Have you built an Ecological Niche Model? If yes\, you have already encountered challenges on data preparation\, or have struggled with issues in models fitting and accuracy. This course will teach you how to overcome these challenges and improve the accuracy of your ecological niche models. By the end of 5-day practical course\, you will have the capacity to filter records and select your variables with variance inflation factor; to test effect of Maxent regularization parameter in models performance; to validate models performance and accuracy; to perform MESS analysis\, null models\, and mechanistic models\, as well as to build your “virtual species”. \nEcological niche\, species distribution\, habitat distribution\, or climatic envelope models are different names for mechanistic and correlative models\, which are empirical or mathematical approaches to the ecological niche of a species. These methods relate different types of ecogeographical variables (environmental\, topographical\, human) to species physiological data or geographical locations\, in order to identify the factors limiting and defining the species&#39; niche. ENMs have become popular because of their efficiency in the design and implementation of conservation management. \nBy the end of 5-day practical course should be able to: \n\nfilter records and select your variables with variance inflation factor;\ntest the effect of Maxent regularization parameter in models performance;\nvalidate models performance and accuracy;\nperform MESS analysis\, null models\, and mechanistic models\, as well as to build your “virtual species”.\n\nStudents will learn to use functions implemented in the packages “usdm”; “dismo”; “ENMEval”; “SDMvspecies”; “spThin”; and “NicheMapper” among others. \n			\n				\n				\n				\n				\n				Intended Audiences\n				This course is orientated to PhD and MSc students\, as well as other students and researchers working on biogeography\, spatial ecology\, or related disciplines\, with experience in ecological niche models. \n			\n				\n				\n				\n				\n				Venue\n				Delivered remotely\n			\n				\n				\n				\n				\n				Course Details\n				Time Zone – Portugal (GMT+!) local time \nAvailability – 24 places \nDuration – 5 days\, 7 hours a day \nContact hours – Approx. 35 hours \nECT’s – Equal to 3ECT’s \nLanguage – English \n			\n				\n				\n				\n				\n				Teaching Format\n				The course will be mainly practical\, with some theoretical lectures. All modelling processes and calculations will be performed with R\, the free software environment for statistical computing and graphics (http://www.r-project.org/). Students will learn to use functions implemented in the packages “usdm”; “dismo”; “ENMEval”; “SDMvspecies”; “spThin”; and “NicheMapper” among others. \n			\n				\n				\n				\n				\n				Assumed quantitative knowledge\n				A basic understanding of ecological niche models and biogeography in general is required\, thus we will assume the attendees know how to run an ecological niche model. \n			\n				\n				\n				\n				\n				Assumed computer background\n				Solid knowledge in Geographical Information Systems and R statistical package is necessary. It is also essential to have experience in ecological niche models. We will focus exclusively on advanced methods. If you need an introductory course on ecological niche models\, please consider attending our basic course on PRStatistics (www.prstats.org). \n			\n				\n				\n				\n				\n				Equipment and software requirements\n				\nA laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs\, Macs\, and Linux computers. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/. \n\n\nAll the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed\, and a full list of required packages will be made available to all attendees prior to the course. \n\n\nA working webcam is desirable for enhanced interactivity during the live sessions\, we encourage attendees to keep their cameras on during live zoom sessions. \n\n\nAlthough not strictly required\, using a large monitor or preferably even a second monitor will improve he learning experience \n\n\nDownload R \n\n\nDownload RStudio \n\n\nDownload Zoom \n\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n	\n		Tickets	\n	\n	\n	\n	\n	\n	\n		The numbers below include tickets for this event already in your cart. Clicking "Get Tickets" will allow you to edit any existing attendee information as well as change ticket quantities.	\n\n\n\n	\n	\n		HMSC01 ONLINE\n	\n	HMSC01 ONLINE\n\n	\n		\n		\n				\n					£\n					450.00\n				\n						\n\n			\n			Unlimited	\n				\n			\n				Open the ticket description.\n				More			\n			\n				Close the ticket description.\n				Less			\n	\n	\n\n			\n			\n	Decrease ticket quantity for HMSC01 ONLINE\n	-\n		\n	\n		Quantity	\n	\n\n		\n	Increase ticket quantity for HMSC01 ONLINE\n	+\n		\n	\n				\n		\n\n		\n	\n		Quantity:	\n	0\n\n	\n	\n		Total:	\n	\n		\n				\n					£\n					0.00\n				\n				\n\n			\n	Get Tickets\n	\n\n	\n		\n	\n\n		\n	\n\n		\n	\n\n	\n\n\n\n\n\n	\n\n\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				PLEASE READ – CANCELLATION POLICY \nCancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered\, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.\n			\n				\n				\n				\n				\n				\nIf you are unsure about course suitability\, please get in touch by email to find out more oliverhooker@prstatistics.com \n\n			\n			\n				\n				\n				\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				COURSE PROGRAMME\n  \n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Monday 1st\n				Day 1 – Classes from 09:30 to 17:30 \n\nENM guide: how to model\nENM R packages.\nSources of environmental variables using geodata package.\nGetting species records with geodata package.\n\n			\n				\n				\n				\n				\n				Tuesday 2nd\n				Day 2 – Classes from 09:30 to 17:30 \n\nVariable selection with variance inflation factor (VIF) and usdm packages.\nChoosing the correct study area.\nFiltering records using usdm/spThin packages.\nChoosing pseudo-absences with Biomod2 package.\n\n			\n				\n				\n				\n				\n				Wednesday 3rd\n				Day 3 – Classes from 09:30 to 17:30 \n\nSplit records in training and test with ENMeval package.\nTest effect of Maxent regularization parameter.<.li>\nComparing correlative models with AIC\, with ENMeval package.\n\n			\n				\n				\n				\n				\n				Thursday 4th\n				Day 4 – Classes from 09:30 to 17:30 \n\nMESS practice with Biomod2 package.\nValidate models null models.\nVirtualSpecies virtualspecies packages.\n\n			\n				\n				\n				\n				\n				Friday 5th\n				Day 5 – Classes from 09:30 to 17:30 \n\nMechanistic model NicheMapper packages.\n\n			\n			\n				\n				\n				\n				\n				\n				\n					Dr. Neftali Sillero\n					\n					Neftalí Sillero works in the analysis and identification of biodiversity spatial patterns\, from species to populations and individuals. For this\, he uses four powerful tools to better understand how space influence biodiversity: Geographical Information Systems\, Remote Sensing\, Ecological Niche Modelling\, and Spatial Statistics. His main areas of research are: application of new technologies on species’ distributions atlases\, ecological modelling of species’ ranges\, identification of biogeographical regions and species’ chorotypes\, mapping and modelling road-kill hotspots\, and spatial analyses of home ranges. \nHe has more than 10 years’ experience working in ecological niche models. He has authored >70 peer reviewed publications and he is since 2007 Chairman of the Mapping Committee of the Societas Herpetologica Europaea\, where he is the PI of the NA2RE project (www.na2re.ismai.pt)\, the New Atlas of Amphibians and Reptiles of Europe \nPersonal website \nWork Webpage \nResearchGate \nGoogleScholar \n					\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Teaches\n				\nEcological Niche Modelling Using R (ENMR)\nAdvanced Ecological Niche Modelling Using R (ANMR)\nGIS And Remote Sensing Analyses With R (GARM)\n\n			\n				\n				\n				\n				\n				Teaches\n				\nEcological Niche Modelling Using R (ENMR)\nAdvanced Ecological Niche Modelling Using R (ANMR)\nGIS And Remote Sensing Analyses With R (GARM)\n\n			\n			\n				\n				\n				\n				\n				\n				\n					Dr. Salvador Arenas-Castro\n					\n					Dr. Salvador Arenas-Castro is a broad-spectrum ecologist with interesting in differentintegrative perspective of the fundamental ecology\, macroecology and biogeographywith their both application and relationship to climate and land management. He is alsoexploring other research sources in agroecology\, forestry\, spatial ecology\, andecoinformatics\, all addressed by explicitly considering the spatial component ofecological processes\, mainly applying spatially explicit modelling approaches\, GIS andremote sensing techniques. Please check his webpage for further information:https://salvadorarenascastro.wordpress.com \nGoogle Scholar: https://scholar.google.com/citations?user=UAYiB5UAAAAJ&hl=es&oi=aoResearchGate: https://www.researchgate.net/profile/Salvador-Arenas-Castro
URL:https://prstats.org/course/rna-seq-analysis-rnaa01/
LOCATION:Delivered remotely (United Kingdom)\, Western European Time Zone\, United Kingdom
CATEGORIES:Home Courses,Live Online Courses
ATTACH;FMTTYPE=image/png:https://prstats.org/wp-content/uploads/2025/09/RNAA01.png
GEO:53.1423672;-7.6920536
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260127
DTEND;VALUE=DATE:20260130
DTSTAMP:20260419T111206
CREATED:20240613T125347Z
LAST-MODIFIED:20260408T105442Z
UID:10000452-1769472000-1769731199@prstats.org
SUMMARY:Species Distribution Modelling With Bayesian Statistics (SDMB07)
DESCRIPTION:Joint Species Distribution Modelling (JSDM) using HMSC: A Hierarchical Modelling Approach (JSDM01)\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Event Date \nTuesday\, September 30th\, 2025\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n					\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Course Format\nThis is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendeesthrough the accompanying computer practicals via video link\, so a good internet connection isessential. \nTime Zone\nTIME ZONE – Portugal (GMT+1) local time – however all sessions will be recorded and made available allowing attendees from different time zones to follow. \nPlease email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you. \n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				About This Course\n				This course focuses on the use of BART (Bayesian Additive Regression Trees) for modellingspecies’ geographical distributions based on occurrence data and environmental variables. BART is a relatively recent technique that shows very promising results in the field of species distribution and ecological niche modelling (SDM / ENM)\, as it produces accurate predictions (considering various aspects of model performance) without overfitting to noise or to special cases in the data. Additionally\, BART allows mapping the uncertainty and credible intervals associated to each local prediction. \nThe course includes a combination of theoretical lectures and hands-on practicals in R\, as well asopen discussions about models and data for SDM applications. The practicals go through acomplete worked example\, from data preparation to model output analysis\, with annotated Rscripts that can be adapted on-the-spot by participants to work on their own species of interest.Along the course\, the instructor is available for constant feedback and orientation on participants’; outputs and interpretations. \n			\n				\n				\n				\n				\n				Intended Audiences\n				The course is aimed at students\, researchers and practitioners with an interest in implementing\nbest practices and state-of-the-art methods for modelling species’ distributions or ecological\nniches\, in an automated and reproducible way.\n			\n				\n				\n				\n				\n				Venue\n				Delivered remotely\n			\n				\n				\n				\n				\n				Course Details\n				Availability – 18 places \nDuration – 3 days \nContact hours – Approx. 12 hours live\, plus remote assistance via Slack from the first day to the\nweekday after the course. \nECT’s – Equal to 1.5 ECT’s \nLanguage – English\n			\n				\n				\n				\n				\n				Teaching Format\n				This course runs along 3 days\, each with a 4-hour live online session. Each session is divided into4 parts\, alternating between theoretical lectures and hands-on practicals. Annotated scripts areprovided and instructor assistance is available\, both during the live sessions (on Zoom) andwhenever possible the rest of the day (on Slack)\, until the weekday after the course.Live sessions will be video-recorded\, uploaded to a video hosting website as soon as possible aftereach session\, and remain available for one month after the course. \n			\n				\n				\n				\n				\n				Assumed quantitative knowledge\n				Participants should know what species distribution or ecological niche models (SDM / ENM) are\,\nand ideally have some previous experience with the basics. Previous knowledge of Bayesian\nstatistics is not required.\n			\n				\n				\n				\n				\n				Assumed computer background\n				Participants should have some previous experience with R\, including package installation and\nbasic data handling\, although commented scripts will be provided for the entire course.\n			\n				\n				\n				\n				\n				Equipment and software requirements\n				\nParticipants must use a computer with a good internet connection\, a working recent version or R (and ideally also RStudio)\, and recent versions of some R packages whose installation instructions will be sent a few days before the course. A working webcam is desirable for enhanced interactivity during the live sessions. Some computation power is required for modelling large datasets\, although the provided example data (and suggested subsets of participants’ data) can run on an ordinary laptop. \n\n\nDownload R \n\n\nDownload RStudio \n\n\nDownload Zoom \n\n \n \n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n	\n		Tickets	\n	\n	\n	\n	\n	\n	\n		The numbers below include tickets for this event already in your cart. Clicking "Get Tickets" will allow you to edit any existing attendee information as well as change ticket quantities.	\n\n\n\n	\n	\n		HMSC01 ONLINE\n	\n	HMSC01 ONLINE\n\n	\n		\n		\n				\n					£\n					450.00\n				\n						\n\n			\n			Unlimited	\n				\n			\n				Open the ticket description.\n				More			\n			\n				Close the ticket description.\n				Less			\n	\n	\n\n			\n			\n	Decrease ticket quantity for HMSC01 ONLINE\n	-\n		\n	\n		Quantity	\n	\n\n		\n	Increase ticket quantity for HMSC01 ONLINE\n	+\n		\n	\n				\n		\n\n		\n	\n		Quantity:	\n	0\n\n	\n	\n		Total:	\n	\n		\n				\n					£\n					0.00\n				\n				\n\n			\n	Get Tickets\n	\n\n	\n		\n	\n\n		\n	\n\n		\n	\n\n	\n\n\n\n\n\n	\n\n\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				PLEASE READ – CANCELLATION POLICY \nCancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered\, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.\n			\n				\n				\n				\n				\n				\nIf you are unsure about course suitability\, please get in touch by email to find out more oliverhooker@prstatistics.com \n\n			\n			\n				\n				\n				\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				COURSE PROGRAMME\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Tuesday 30th\n				Day 1 – Classes from 14:00 –  18:00 \n\nModule 1a: Obtain and process data\, including species presences and environmental variables\nPractical\nModule 1b: Determine an adequate spatial resolution and extent for modelling\nPractical\n\n			\n				\n				\n				\n				\n				Wednesday 1st\n				Day 2 – Classes from 14:00 –  18:00 \n\nModule 2a: Build a species distribution model with BART and obtain predictions of environmental favorability\, with credibility intervals and associated uncertainty\nPractical\nModule 2b: Evaluate and cross-validate the model\, assessing various aspects of predictive ability\nPractical\n\n  \n			\n				\n				\n				\n				\n				Thursday 2nd\n				Day 3 – Classes from 14:00 –  18:00 \n\n Module 3a: Quantify variable contributions and try out different methods for selecting relevant variables\nPractical\nModule 3b: Plot and map the species’ partial response to each variable\nPractical\n\n			\n			\n				\n				\n				\n				\n				\n				\n					Dr. Marcia Barbosa\n					\n					Márcia is an experienced researcher and instructor in biogeography and macroecology\, particularly in geographic information systems and species distribution modelling. She’s also a reviewer and editor for scientific journals and funding agencies\, and a promoter and developer of free and open-source software implementing transparency\, reproducibility and best practices. You can see her publication list at her website or at Publons/ResearcherID\, Scopus\, ORCID\, Google Scholar\, or ResearchGate. \nResearch Gate \nGoogle Scholar \nORCID \nGitHub \nHomepage
URL:https://prstats.org/course/species-distribution-modelling-with-bayesian-statistics-sdmb07/
LOCATION:Delivered remotely (United Kingdom)\, Western European Time Zone\, United Kingdom
CATEGORIES:All Live Courses,Home Courses,Live Online Courses
ATTACH;FMTTYPE=image/jpeg:https://prstats.org/wp-content/uploads/2024/06/SDMB07-1.jpg
GEO:53.1423672;-7.6920536
END:VEVENT
END:VCALENDAR