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Bioinformatics Training

Bioinformatics course timetable

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Thu 20 Sep – Thu 17 Jan 2019

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September 2018

Mon 24
Data Carpentry in R (1 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

In many domains of research the rapid generation of large amounts of data is fundamentally changing how research is done. The deluge of data presents great opportunities, but also many challenges in managing, analyzing and sharing data.

Data Carpentry workshops are designed to teach basic concepts, skills and tools for working more effectively with data, using a combination of tools with a main focus in R. The workshop is aimed at researchers in the life sciences at all career stages and is designed for learners with little to no prior knowledge of programming, shell scripting, or command line tools.

This course is organized in collaboration with ElixirUK and the Software Sustainability Institute.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

Tue 25
Data Carpentry in R (2 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

In many domains of research the rapid generation of large amounts of data is fundamentally changing how research is done. The deluge of data presents great opportunities, but also many challenges in managing, analyzing and sharing data.

Data Carpentry workshops are designed to teach basic concepts, skills and tools for working more effectively with data, using a combination of tools with a main focus in R. The workshop is aimed at researchers in the life sciences at all career stages and is designed for learners with little to no prior knowledge of programming, shell scripting, or command line tools.

This course is organized in collaboration with ElixirUK and the Software Sustainability Institute.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

Wed 26
An Introduction to Machine Learning (1 of 3) [Full] 13:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Machine learning gives computers the ability to learn without being explicitly programmed. It encompasses a broad range of approaches to data analysis with applicability across the biological sciences. Lectures will introduce commonly used algorithms and provide insight into their theoretical underpinnings. In the practicals students will apply these algorithms to real biological data-sets using the R language and environment.

Please be aware that the course syllabus is currently being updated following feedback from the last event; therefore the agenda below will be subjected to changes.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

Thu 27
An Introduction to Machine Learning (2 of 3) [Full] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Machine learning gives computers the ability to learn without being explicitly programmed. It encompasses a broad range of approaches to data analysis with applicability across the biological sciences. Lectures will introduce commonly used algorithms and provide insight into their theoretical underpinnings. In the practicals students will apply these algorithms to real biological data-sets using the R language and environment.

Please be aware that the course syllabus is currently being updated following feedback from the last event; therefore the agenda below will be subjected to changes.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

Fri 28
An Introduction to Machine Learning (3 of 3) [Full] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Machine learning gives computers the ability to learn without being explicitly programmed. It encompasses a broad range of approaches to data analysis with applicability across the biological sciences. Lectures will introduce commonly used algorithms and provide insight into their theoretical underpinnings. In the practicals students will apply these algorithms to real biological data-sets using the R language and environment.

Please be aware that the course syllabus is currently being updated following feedback from the last event; therefore the agenda below will be subjected to changes.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

October 2018

Wed 17
Introduction to Unix shell new [Places] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course offers an introduction to working with Linux. We will describe the Linux environment so that participants can start to utilize command-line tools and feel comfortable using a text-based way of interacting with a computer. We will take a problem-solving approach, drawing on types of tasks commonly encountered by Linux users when processing text files.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to Book or register Interest by linking here.

Thu 18
High Performance Computing: An Introduction [Places] 09:30 - 16:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

The course aims to give an introductory overview of High Performance Computing (HPC) in general, and of the facilities of the High Performance Computing Service (HPCS) available at the University of Cambridge.

Practical examples of using the HPCS clusters will be used throughout, although it is hoped that much of the content will have applicability to systems elsewhere.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

Wed 24
An Introduction to Solving Biological Problems with R (1 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

R is a highly-regarded, free, software environment for statistical analysis, with many useful features that promote and facilitate reproducible research.

In this course, we give an introduction to the R environment and explain how it can be used to import, manipulate and analyse tabular data. After the course you should feel confident to start exploring your own dataset using the materials and references provided.

The course website providing links to the course materials is here.

Please note that although we will demonstrate how to perform statistical analysis in R, we will not cover the theory of statistical analysis in this course. Those seeking an in-depth explanation of how to perform and interpret statistical tests are advised to see the list of Related courses. Moreover, those with some programming experience in other languages (e.g. Python, Perl) might wish to attend the follow-on Data Analysis and Visualisation in R course.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Thu 25
An Introduction to Solving Biological Problems with R (2 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

R is a highly-regarded, free, software environment for statistical analysis, with many useful features that promote and facilitate reproducible research.

In this course, we give an introduction to the R environment and explain how it can be used to import, manipulate and analyse tabular data. After the course you should feel confident to start exploring your own dataset using the materials and references provided.

The course website providing links to the course materials is here.

Please note that although we will demonstrate how to perform statistical analysis in R, we will not cover the theory of statistical analysis in this course. Those seeking an in-depth explanation of how to perform and interpret statistical tests are advised to see the list of Related courses. Moreover, those with some programming experience in other languages (e.g. Python, Perl) might wish to attend the follow-on Data Analysis and Visualisation in R course.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

November 2018

Mon 12
Using the Ensembl Genome Browser [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

The Ensembl Project provides a comprehensive and integrated source of annotation of, mainly vertebrate, genome sequences. This workshop offers a comprehensive practical introduction to the use of the Ensembl genome browser as well as essential background information.

This course will focus on the vertebrate genomes in Ensembl, however much of what will be covered is also applicable to the non-vertebrates (plants, bacteria, fungi, metazoa and protists) in Ensembl Genomes.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Wed 14
Introduction to Scientific Figure Design [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course provides a practical guide to producing figures for use in reports and publications.

It is a wide ranging course which looks at how to design figures to clearly and fairly represent your data, the practical aspects of graph creation, the allowable manipulation of bitmap images and compositing and editing of final figures.

The course will use a number of different open source software packages and is illustrated with a number of example figures adapted from common analysis tools.

Further information and access to the course materials is here.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Wed 21
Ontologies and ontology-based data analysis [Places] 10:00 - 15:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Ontologies have long provided a core foundation in the organization of biomedical entities, their attributes, and their relationships. With over 500 biomedical ontologies currently available there are a number of new and exciting opportunities emerging in using ontologies for large scale data sharing and data analysis.

This tutorial will help you understand what ontologies are and how they are being used in computational biology and bioinformatics. It will include hands-on examples and exercises and an introduction to Onto2Vec and OPA2Vec, two methods that can be used to learn semantic similarity measures in a data- and application-driven way.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

Thu 29
An Introduction to Solving Biological Problems with Python (1 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core aspects of Python illustrated by a series of example programs. Upon completion of the course, attentive participants will be able to write simple Python programs and customize more complex code to fit their needs.

Course materials are available here.

Please note that the content of this course has recently been updated. This course now mostly focuses on core concepts including Python syntax, data structures and reading/writing files. Functions and modules are now the focus of a new 1-day course, Working with Python: functions and modules.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

Fri 30
An Introduction to Solving Biological Problems with Python (2 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core aspects of Python illustrated by a series of example programs. Upon completion of the course, attentive participants will be able to write simple Python programs and customize more complex code to fit their needs.

Course materials are available here.

Please note that the content of this course has recently been updated. This course now mostly focuses on core concepts including Python syntax, data structures and reading/writing files. Functions and modules are now the focus of a new 1-day course, Working with Python: functions and modules.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

December 2018

Mon 10
Using CellProfiler and CellProfiler Analyst to analyse biological images (1 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Microscopy experiments have proven to be a powerful means of generating information-rich data for biological applications. From small-scale microscopy experiments to time-lapse movies and high-throughput screens, automatic image analysis is more objective and quantitative and less tedious than visual inspection.

This course will introduce users to the free open-source image analysis program CellProfiler and its companion data exploration program CellProfiler Analyst. We will show how CellProfiler can be used to analyse a variety of types of imaging experiments. We will also briefly discuss the basic principles of supervised machine learning with CellProfiler Analyst in order to score complex and subtle phenotypes.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Tue 11
Using CellProfiler and CellProfiler Analyst to analyse biological images (2 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Microscopy experiments have proven to be a powerful means of generating information-rich data for biological applications. From small-scale microscopy experiments to time-lapse movies and high-throughput screens, automatic image analysis is more objective and quantitative and less tedious than visual inspection.

This course will introduce users to the free open-source image analysis program CellProfiler and its companion data exploration program CellProfiler Analyst. We will show how CellProfiler can be used to analyse a variety of types of imaging experiments. We will also briefly discuss the basic principles of supervised machine learning with CellProfiler Analyst in order to score complex and subtle phenotypes.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Fri 14
Analysis of DNA Methylation using Sequencing [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course will cover all aspects of the analysis of DNA methylation using sequencing, including primary analysis, mapping and quality control of BS-Seq data, common pitfalls and complications.

It will also include exploratory analysis of methylation, looking at different methods of quantitation, and a variety of ways of looking more widely at the distribution of methylation over the genome. Finally the course will look at statistical methods to predict differential methylation.

The course will be comprised of a mixture of theoretical lectures and practicals covering a range of different software packages.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

January 2019

Wed 9
Statistics for Biologists in R (1 of 4) [Places] 13:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course is intended to provide a strong foundation in practical statistics and data analysis using the R software environment. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences using the R software package.

In this course we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to multiple linear regression. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory.

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Thu 10
Statistics for Biologists in R (2 of 4) [Places] 13:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course is intended to provide a strong foundation in practical statistics and data analysis using the R software environment. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences using the R software package.

In this course we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to multiple linear regression. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory.

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Wed 16
Statistics for Biologists in R (3 of 4) [Places] 13:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course is intended to provide a strong foundation in practical statistics and data analysis using the R software environment. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences using the R software package.

In this course we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to multiple linear regression. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory.

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Thu 17
Statistics for Biologists in R (4 of 4) [Places] 13:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course is intended to provide a strong foundation in practical statistics and data analysis using the R software environment. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences using the R software package.

In this course we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to multiple linear regression. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory.

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.



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Training events

October 2018

10 10
ENA Sequence Retrieval
European Bioinformatics Institute (EMBL-EBI) - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
10th Oct

This training will introduce ENA (European Nucleotide Archive) users to powerful search and retrieval methods available for annotated sequences, genomes, raw data and metadata, as well as download options from the ENA browser and an introduction to the various ENA browser tools. There will also be a section on cross references and how to retrieve accessions for other resources linked to the primary data in ENA. There will be time for users to present their own use cases or request specific help with their own queries.

First come, first served

17 17
Ensembl browser workshop, EMBL-EBI, 17 October 2018
European Bioinformatics Institute (EMBL-EBI) - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
17th Oct

Work with the Ensembl Outreach team to get to grips with the Ensembl browser, accessing gene, variation, comparative genomics and regulation data, and mine these data with BioMart.

First come, first served

November 2018

13 13
Exploring Biological Sequences
European Bioinformatics Institute (EMBL-EBI) - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
13th 15th Nov

This course will introduce you to approaches used for finding, analysing and using biological sequences.

First come, first served

13th

January 2019

22 22
Bioinformatics for Discovery
European Bioinformatics Institute (EMBL-EBI) - Training Room 2 - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
22nd 23rd Jan

A Master’s level short course aimed at providing discovery scientists from a range of fields (e.g. agri-food, pharma and consumer goods) with the skills and knowledge required to apply bioinformatics techniques in their everyday work.

Open application with selection

22nd

February 2019

12 12
Introduction to Multiomics Data Integration
European Bioinformatics Institute (EMBL-EBI) - Training Room 2 - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
12th 15th Feb

This course will provide participants with biological examples of data integration, and the challenges that researchers face. The course will focus on the use of public data resources and open access tools for enabling integrated working, with an emphasis on data visualisation.

Open application with selection

12th 26 26
Bioinformatics Resources for Protein Biology
European Bioinformatics Institute (EMBL-EBI) - Training Room 1 - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
26th 28th Feb

Are you aware of the wide range of protein data resources that can easily be accessed and explored to enhance your research? Do you want to know more about the sequence of your protein and its functions? Wondered whether a structure of your protein exists and how to explore it? Want to know more about the potential complexes and reaction pathways your protein of interest is involved in, giving you a better overview of its biological context?

First come, first served

26th

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CSED 2015 programme

CSED page


COMPUTING FOR RESEARCH
Introduction to NVivo
An Introduction to R  [NEW]
Intermediate Workshop on R [NEW]
An Introduction to PASW (SPSS) [NEW]
Basic Data Analysis PASW (SPSS) [NEW]
Advanced Data Analysis I PASW (SPSS) [NEW]
Advanced Data Analysis II PASW (SPSS) [NEW]
Introduction to Linux [NEW]
Introduction to High Powered Computing [NEW]
Matlab (Online Service) [NEW]

 

Introduction to NVivo

DATE & TIME: Tuesdays 18 & 25 November 2014, 09.30-12.30
REPEATED: Wednesdays 4 & 11 February 2015, 13.30-16.30
REPEATED: Fridays 8 & 15 May 2015, 09.30-12.30
TUTOR: Steve Oldfield, CSED
DURATION: Two half days
VENUE: CSED IT Training Room, 02.01, Library
DETAILS: Nvivo is a software package which makes the task of analysing qualitative data easier. ITCS has arranged a site licence which some Schools at UEA have bought into. It is expected that we will be using version 10 for this course. This course provides a step-by-step introduction to using NVivo for those with little or no experience of it (though some familiarity with analysing qualitative data will be an advantage). Demonstration data will be used, though the techniques and organising principles can be applied to any qualitative data. The course focuses on basic use of the software package; it is not a research methods course.
ADDITIONAL INFORMATION: Participants are expected to attend both parts. A general familiarity with the use of Windows features such as menus, toolbars and dialogue boxes is a prerequisite. Course materials are provided in-session.

[Go to Top of Page]     [Online Course Booking Form]


An Introduction to R [NEW]

DATE & TIME: Wednesday 8 October 2014, 12.00-14.00
VENUE: Room 0.24, Chancellors Drive Annexe
REPEATED: Wednesday 18 February 2015, 12.00-14.00
VENUE: ARTS 1.02
SESSION LEADERS:
Gareth Janacek, CMP
DURATION: 2 hours
RDF Domains: A1, A3
DETAILS: This basic introduction to R aims to get you up and running. We assume some very basic computer skills and a familiarity with data. The topics we expect to cover are;

  • What is R?
  • Basics
  • Preparing and Importing Your Data
  • The Help Files
  • Finding and loading R Packages
  • Graphics
  • Record Keeping
  • Problems/Getting help
  • Examples of analyses: regression and generalised linear models
  • Multivariate techniques (if time permits)

ADDITIONAL INFORMATION: Please feel free to bring your own laptop. The data examples used will be available on Blackboard.

[Go to Top of Page]     [Online Course Booking Form]


Intermediate Workshop on R [NEW]

DATE & TIME: Tuesday 11 November 2014, 12.00-14.00
VENUE: BIO 0.12
REPEATED: Wednesday 13 May 2015, 12.00-14.00
VENUE: ARTS 1.02
SESSION LEADER: Gareth Janacek, CMP
DURATION: 2 hours
RDF Domains: A1, A3
DETAILS: The aim of this session is to show how one can use R to perform statistical analyses. This is a huge subject area and we shall aim to show what is available without delving too far into de   tails. Do feel free to bring your own laptop. The approach is example driven and quite practical.

We would aim to cover:

  • Multivariate analysis
  • PCA
  • Factor Analysis
  • Discriminant analysis
  • Time Series Analysis
  • Time series class
  • Plots
  • Time domain modelling – Forecasting
  • The frequency domain
  • Graphics
  • The basic graphic system, devices and output
  • Trellis graphics
  • GGplot
  • Bayesian Methods
  • Introduction and the LearnBayes pac  kage
  • MCMC
  • R functions for Bayesian inference using lm, glm, mer and polr objects.
  • Point out packages that link R to other Bayesian sampling engines such as JAGS , OpenBUGS , and WinBUGS
  • Survival Analysis
  • Censoring
  • Kaplan –Meier
  • Cox Models

We aim to have at least one example data set in each case.

ADDITIONAL INFORMATION: Feel free to bring your own laptop

[Go to Top of Page]     [Online Course Booking Form]


Introduction to PASW (SPSS) [NEW]

DATE & TIME: Wednesday 14 January 2015, 09.30-12.30
VENUE: Arts, 1.02
SESSION LEADER: Simon Poulton, BIO
DURATION: A half day
RDF Domains: A1, A3
DETAILS:This session introduces you to the PASW (SPSS) statistical software and will cover ways to create and interpret histograms, bar charts and scatter plots using the interactive “Chart Builder”, as well as two main themes;

  • Getting started, including an introduction to the PASW environment (windows & settings), definition of variables, opening and saving PASW files and importing data from other software packages.
  • Exploring your data, including how to create summary statistics for your variables and the creation of frequency tables and cross-tabulations between variables.

ADDITIONAL INFORMATION: There are no attendance requirements for this session, prior knowledge of PASW (SPSS) is not essential, and you do not have to attend all four sessions.  The emphasis is on practical use of PASW rather than statistical theory.  The session will have a strong graphical emphasis and include ‘hands-on’ exercises as well as opportunities for feedback and Q&As.

[Go to Top of Page]     [Online Course Booking Form]


Basic Data Analysis PASW (SPSS) [NEW]

DATE & TIME: Thursday 15 January 2015, 09.30-12.30
VENUE: BIO, 0.12
SESSION LEADERS: Simon Poulton, BIO
DURATION: A half day
RDF Domains: A1, A3
DETAILS: This session assumes that you have used PASW before and have a basic understanding of statistical analysis and testing methods. It will continue the practical use of PASW and show you how to manage, extract and analyse data as well as generate graphical techniques provided in the “Chart Builder”.
ADDITIONAL INFORMATION: To benefit from this session you should be familiar with using PASW.  If you understand and have successfully completed statistical analyses such as ANOVA and linear regression then this course may not be suitable. The emphasis is on practical use of PASW rather than statistical theory. The session will have a strong graphical emphasis and include ‘hands-on’ exercises as well as opportunities for feedback and Q&As.

[Go to Top of Page]     [Online Course Booking Form]

 


Advanced Data Analysis I PASW (SPSS) [NEW]

DATE & TIME: Wednesday 11 March 2015, 09.30-12.30
VENUE: Arts, 1.02
SESSION LEADER: Simon Poulton, BIO
DURATION: A half day
RDF Domains: A1, A3
DETAILS: This session will introduce the concepts of Analysis-of-Variance, Linear Regression and General Linear Models, how they are run and interpreted in PASW. It will cover advanced PASW data handling methods; transposing data and the comprehensive two-stage process for data validation, including the detection of outliers. It introduces the concepts of ANOVA, then moves forward to two-way and multi-way ANOVA, with particular emphasis on how to arrange your data and explore methods of correlation and multiple regression models.
ADDITIONAL INFORMATION: To benefit from this session you should be well-versed in the use of PASW (SPSS) or other statistical software and confident in manipulating data, although perhaps unsure how to achieve this in PASW. You will require an understanding of concepts such as the sums-of-squares and variances, confidence intervals and how to interpret p-values. If you possess extensive experience in using GLMs for linear modelling, then this course may not be suitable. The emphasis is on practical use of PASW rather than statistical theory. The session will have a strong graphical emphasis and include ‘hands-on’ exercises as well as opportunities for feedback and Q&As.

 

[Go to Top of Page]     [Online Course Booking Form]

 


Advanced Data Analysis II PASW (SPSS) [NEW]

DATE & TIME: Wednesday 27 May 2015, 09.30-12.30
VENUE: Arts, 1.02
SESSION LEADER: Simon Poulton
DURATION: A half day
RDF Domains: A1, A3
DETAILS: This session continues the theme of practical use of the software. It explores the importance of residuals and diagnostic tests in ANOVA and regression models and will also cover a brief introduction to Analysis-of-Covariance (ANCOVA). Emphasis will be on how to organise your data and specify models using the GLM dialogue boxes. It will explore the use of mixed models and repeated-measures models and outline how they are implemented and defined in PASW. If you are curious about residuals plots, post-hoc testing or more complex types of linear models then this session may be for you. There will be a strong emphasis on the interpretation of PASW outputs.
ADDITIONAL INFORMATION: You should possess considerable experience of manipulating data and an understanding of basic linear modelling techniques. Familiarity with interpreting the outputs from simple ANOVA and regression models is also required. The emphasis is on practical use of PASW rather than statistical theory. The session will have a strong graphical emphasis and include ‘hands-on’ exercises as well as opportunities for feedback and Q&As.

[Go to Top of Page]     [Online Course Booking Form]


Introduction to Linux [NEW]

RDF Domains: A1, A3
DETAILS: Linux is a powerful and versatile open source operating system frequently found powering desktop computers and servers, including the UEA High Performance Computing Cluster. In one-to-one or small group sessions we will work through the fundamental skills needed to begin working with Linux tailored to the individual: from familiarising participants with the working environment, using common commands and file management to more advanced usage and scripting.
ADDITIONAL INFORMATION: This course is held on a one-to-one basis. For further information and to register your interest, please contact hpc.admin@uea.ac.uk

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Introduction to High Powered Computing [NEW]

RDF Domains: A1, A3
DETAILS: Do you have a computational element to your research? In a one-to-one session we will introduce UEA’s HPC cluster and discuss how it can benefit your research looking at your own specific computational requirements. We will go through the initial steps on using the HPC cluster and help you get started with your own task.
ADDITIONAL INFORMATION: This course is held on a one-to-one basis. For further information and to register your interest, please contact hpc.admin@uea.ac.uk

[Go to Top of Page]


Matlab (Online Service) [NEW]

RDF Domains: A1, A3
DETAILS:

Matlab Fundamentals

This online course provides a comprehensive introduction to the MATLAB technical computing environment and is intended for beginners and those looking for a review. No prior programming experience or knowledge of MATLAB is necessary. The course is structured to allow thorough assimilation of ideas through hands-on examples and exercises. MATLAB competency is developed in a natural way, with an emphasis on practical application. Themes of data analysis, visualization, modelling, and programming are explored throughout the course.

Topics include:

  • Working with the MATLAB user interface
  • Entering commands and creating variables
  • Performing analysis on vectors and matrices
  • Visualizing vector and matrix data
  • Working with data files
  • Working with data types
  • Automating commands with scripts
  • Writing programs with logic and flow control
  • Writing functions

Matlab for Data Processing and Visualisation

This course focuses on the details of data management and visualization techniques, from reading arbitrarily formatted text data files to producing customized publication-quality graphics. The course emphasizes creating scripts that extend the basic features provided by MATLAB. Topics include:

  • Importing data
  • Organizing data
  • Visualizing data

Matlab Programming Techniques

This course provides hands-on experience using the features in the MATLAB® language to write efficient, robust, and well-organized code. These concepts form the foundation for writing full applications, developing algorithms, and extending built-in MATLAB capabilities. Details of performance optimization, as well as tools for writing, debugging, and profiling code, are covered. Topics include:

  • Creating robust applications
  • Utilizing development tools
  • Structuring code
  • Structuring data
  • Efficient data management
  • Classes and objects

ADDITIONAL INFORMATION: The Matlab sessions are available to take as an online service. For further information please contact hpc.admin@uea.ac.uk

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