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11 matching courses
Courses per page: 10 | 25 | 50 | 100


Analysis of DNA Methylation using Sequencing Fri 14 Dec 2018   09:30 [Full]

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.

The training room is located on the first floor and there is currently no level access.

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

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. Concepts and strategies for working more effectively with Python are now the focus of a new 2-days course, Data Science in Python.

The training room is located on the first floor and there is currently no level access.

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

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.

This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1).

The training room is located on the first floor and there is currently no level access.

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.

Data Carpentry in R Tue 19 Feb 2019   09:30 [Places]

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.

The training room is located on the first floor and there is currently no level access.

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

Data Science in Python Wed 12 Dec 2018   09:30 [Full]

This course covers concepts and strategies for working more effectively with Python with the aim of writing reusable code, using function and libraries. Participants will acquire a working knowledge of key concepts which are prerequisites for advanced programming in Python e.g. writing modules and classes.

Note: this course is the continuation of the Introduction to Solving Biological Problems with Python; participants are expected to have attended the introductory Python course and/or have acquired some working knowledge of Python. This course is also open to Python beginners who are already fluent in other programming languages as this will help them to quickly get started in Python.

The training room is located on the first floor and there is currently no level access.

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

This course will present a set of R/Bioconductor packages to access, manipulate, visualise and analyse mass spectrometry (MS) and quantitative proteomics data.

The training room is located on the first floor and there is currently no level access.

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

Extracting biological information from gene lists new Fri 1 Mar 2019   09:30 [Full]

Many experimental designs end up producing lists of hits, usually based around genes or transcripts. Sometimes these lists are small enough that they can be examined individually, but often it is useful to do a more structured functional analysis to try to automatically determine any interesting biological themes which turn up in the lists.

This course looks at the various software packages, databases and statistical methods which may be of use in performing such an analysis. As well as being a practical guide to performing these types of analysis the course will also look at the types of artefacts and bias which can lead to false conclusions about functionality and will look at the appropriate ways to both run the analysis and present the results for publication.

Course materials are available here.

The training room is located on the first floor and there is currently no level access.

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.

Introduction to Scientific Figure Design Wed 14 Nov 2018   09:30 [Full]

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.

The training room is located on the first floor and there is currently no level access.

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.

Ontologies and ontology-based data analysis Wed 21 Nov 2018   10:00 [Full]

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.

The training room is located on the first floor and there is currently no level access.

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

Statistics for Biologists in R Wed 9 Jan 2019   13:30 [Full]

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.

This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1).

The training room is located on the first floor and there is currently no level access.

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.

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.

The training room is located on the first floor and there is currently no level access.

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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