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Showing courses 76-100 of 118
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High Performance Computing: An Introduction Thu 18 Oct 2018   09:30 Finished

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.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

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.

A hands-on interactive course that will introduce you to how to analyse genomic sequences in the command line environment. Examples will focus on metagenomics data but the course is suitable to anyone starting to analyze high-throughput sequencing data.

This course will be taught by Dr. Adina Howe from Iowa State University. Her group focuses on integrating traditional microbiology approaches with metagenomics and computational biology as investigative tools to understand environmental microbial populations

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

IAFIG-RMS: Bioimage analysis with Python new charged Mon 9 Dec 2019   09:30 Finished

THIS EVENT IS NOW FULLY BOOKED!

The aim of this 5 days course is to develop motivated participants toward becoming independent BioImage Analysts in an imaging facility or research role. Participants will be taught theory and algorithms relating to bioimage analysis using Python as the primary coding language.

Lectures will focus on image analysis theory and applications. Topics to be covered include: Image Analysis and image processing, Python and Jupyter notebooks, Visualisation, Fiji to Python, Segmentation, Omero and Python, Image Registration, Colocalisation, Time-series analysis, Tracking, Machine Learning, and Applied Machine Learning.

The bulk of the practical work will focus on Python and how to code algorithms and handle data using Python. Fiji will be used as a tool to facilitate image analysis. Omero will be described and used for some interactive coding challenges.

Research spotlight talks will demonstrate research of instructors/scientists using taught techniques in the wild.

This event is organized in collaboration with the Image Analysis Focused Interest Group and is sponsored by the Royal Microscopical Society.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

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.

Image Analysis for Biologists Mon 11 Dec 2017   09:30 Finished

This course will focus on computational methods for analysing cellular images and extracting quantitative data from them. The aim of this course is to familiarise the participants with computational image analysis methodologies, and to provide hands-on training in running quantitative analysis pipelines.

On day 1 we will introduce principles of image processing and analysis, giving an overview of commonly used algorithms through a series of talks and practicals based on Fiji, an extensible open source software package.

On day 2, we will cover time series processing and cell tracking using TrackMate. The afternoon of day two will focus on understanding the basics of deconvolution and colocalisation, using tools in Fiji to look at basic examples of how to apply deconvolution and how to carry out colocalisation analysis in fluorescence microscopy.

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.

Image Analysis for Biologists Mon 24 Jun 2019   09:30 Finished

This course will focus on computational methods for analysing cellular images and extracting quantitative data from them. The aim of this course is to familiarise the participants with computational image analysis methodologies, and to provide hands-on training in running quantitative analysis pipelines.

On day 1 we will introduce principles of image processing and analysis, giving an overview of commonly used algorithms through a series of talks and practicals based on Fiji, an extensible open source software package.

On day 2, we will cover time series processing and cell tracking using TrackMate and advanced image segmentation using Ilastik. Additionally, in the afternoon we will run a study design and data clinic (sign up will be required) for participants that wish to discuss their experiments.

On day 3, we will describe the open Icy platform developed at the Institut Pasteur. Icy is a next-generation, user-friendly software offering powerful acquisition, visualisation, annotation and analysis algorithms for 5D bioimaging data, together with unique automation/scripting capabilities (notably via its graphical programming interface) and tight integration with existing software (e.g. ImageJ, Matlab, Micro-Manager).

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

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.

Image Processing and Visualisation with LithoGraphX new Thu 4 Aug 2016   10:00 Finished

LithoGraphX is a software to visualize, process and analyse 3D images and meshes.

On the first day of this course, we will demonstrate how to use LithoGraphX to visualize, clean and process 2D and 3D images. We will cover: (i) how to extract cell shape from 2D or 3D images by marking the cell wall or membrane, (ii) how to extract key morphological features and (iii) how to use these features to build a cell classifier. The first day is intended for biologists and computer scientists interested in using LithoGraphX.

On the second day, we will see how to write and distribute extensions to LithoGraphX. To this purpose, we will learn more about the internals of LithoGraphX and its API both in C++ and Python. The second day is intended for computer scientists wanting either to write their own algorithm or automate complex protocols.

Participants can choose to register for both days or for individual days, depending on their interest and background knowledge.

The timetable for this event can be found here.

This course is organized in collaboration with Dr Susana Sauret-Gueto from the OpenPlant Lab of the Department of Plant Sciences of the University of Cambridge.

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.

Interpreting the clinical genome with DECIPHER new Fri 8 Jul 2016   09:30 Finished

DECIPHER is a collaborative data sharing and interpretation platform that enables the secure upload, analysis and subsequent sharing of anonymised phenotype-linked patient variant data in rare genetic disorders.

DECIPHER is a worldwide user community of over 250 clinical genetics centres and research groups from over 40 countries that utilise the built-in tools for aiding the interpretation of variants as well as to discover other patients that share similar phenotype and genomic findings.

DECIPHER facilitates collaboration and exchange of information between a global community of clinical centers and researchers leading thereby accelerating discovery and diagnosis. Access to consented anonymised records is free to all users. User accounts are provided to bona-fide clinicians and lab scientists to enable deposition and sharing of anonymised patient data.

The purpose of this half-day workshop is to acquaint participants with the DECIPHER website and database and introduce the various built-in tools for visualisation and interpretation of phenotype-linked genomic variation in anonymised consented patient data. It is hoped that by the end of this workshop, users will be able to carry out effective searches of data, use the built-in genome browser to visualise variation in context of other pathogenic and reference data sources, find other patients with similar variants and shared phenotypes, and identify most likely causes of phenotypic presentation by gene prioritisation.

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.

Galaxy (http://galaxyproject.org/) is an open, web-based platform for data intensive life science research that enables non-bioinformaticians to create, run, tune, and share bioinformatic analyses. The goal of this course is to demonstrate how to use Galaxy to explore RNA-seq data, for expression profiling, and ChIP-seq data, to assess genomic DNA binding sites. You will learn how to perform analysis in Galaxy, and then how to share, repeat, and reproduce your analyses.

The timetable for this event can be found here.

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

Introduction to genome variation analysis using NGS Thu 18 May 2017   09:30 Finished

This course provides an introduction to the analysis of human genome sequence variation with next generation sequencing data (NGS), including:

  • an introduction to genetic variation as well as data formats and analysis workflows commonly used in NGS data analysis;
  • an overview of available analytical tools and discussion of their limitations; and
  • hands-on experience with common computational workflows for analysing genome sequence variation using bioinformatics and computational genomics approaches.

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.

This course provides an introduction to high-throughput sequencing (HTS) data analysis methodologies. Lectures will give insight into how biological knowledge can be generated from RNA-seq, ChIP-seq and DNA-seq experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of RNA-seq, ChIP-seq and DNA-seq data under the guidance of the lecturers and teaching assistants. It is aimed at researchers who are applying or planning to apply HTS technologies and bioinformatics methods in their research.

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 R for Biologists Wed 15 Jan 2020   09:30 [Full]

R is one of the leading programming languages in Data Science. It is widely used to perform statistics, machine learning, visualisations and data analyses. It is an open source programming language so all the software we will use in the course is free. This course is an introduction to R designed for participants with no programming experience. We will start from scratch by introducing how to start programming in R and progress our way and learn how to read and write to files, manipulate data and visualise it by creating different plots - all the fundamental tasks you need to get you started analysing your data. During the course we will be working with one of the most popular packages in R; tidyverse that will allow you to manipulate your data effectively and visualise it to a publication level standard.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

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 RNA-seq and ChIP-seq data analysis Wed 25 Oct 2017   09:30 Finished

The aim of this course is to familiarize the participants with the primary analysis of datasets generated through two popular high-throughput sequencing (HTS) assays: ChIP-seq and RNA-seq.

This course starts with a brief introduction to the transition from capillary to high-throughput sequencing (HTS) and discusses quality control issues, which are common among all HTS datasets. Next, we will present the alignment step and how it differs between the two analysis workflows. Finally, we focus on dataset specific downstream analysis, including peak calling and motif analysis for ChIP-seq and quantification of expression, transcriptome assembly and differential expression analysis for RNA-seq.

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 Fri 11 Oct 2019   09:30 Finished

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 wheelchair or level access available to this level.

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.

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 Interest by linking here.

Introduction to Unix shell new Wed 17 Oct 2018   09:30 Finished

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.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

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 working with UNIX and bash new Thu 6 Feb 2020   09:30 [Full]

Using the Linux operating system and the bash command line interface, we will demonstrate the basic structure of the UNIX operating system and how we can interact with it using a basic set of commands. Applying this, we will learn how to navigate the filesystem, manipulate text-based data and structure simple pipelines out of these commands.

Building on this foundation, the course will use a bioinformatics example to demonstrate how the skills learnt can be applied to connecting to external resources/servers, installing specialist tools and ultimately combining commands into scripts for automation and reproducibility.

This course is targeted at participants with no prior experience working with UNIX-like systems (OSX, Linux) or command line interfaces.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

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.

Molecular Phylogenetics Wed 3 Apr 2019   09:00 Finished

This course will provide training for bench-based biologists to use molecular data to construct and interpret phylogenies, and test their hypotheses. Delegates will gain hands-on practice of using a variety of programs freely-available online and commonly used in molecular studies, interspersed with some lectures.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

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.

Mouse Genome Informatics workshop new Tue 27 Oct 2015   10:00 Finished

Mouse Genome Informatics (MGI) is the international database resource for the laboratory mouse and provides integrated genetic, genomic, and biological data to facilitate the study of human health and disease.

MGI is a free, highly curated resource and offers web and programmatic access to a complete catalogue of mouse genes and genome features, functional annotations, a comprehensive catalogue of mutant and knockout alleles, phenotype and human disease model annotations, gene expression, variation and sequence data.

This workshop will be composed of ~20min overview and ~1 hour hands-on, interactive tutorial.

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

MSt in Genomic Medicine - Advanced bioinformatics Mon 20 Mar 2017   09:30 Finished

This module introduces a deeper exploration of bioinformatics analysis of genomic data, providing a greater understanding of the different approaches to mapping and alignment of genome sequence data, programming and scripting, along with approaches for the detection and analysis of genomic changes, gene expression and network analysis.

Network Visualisation and Analysis of Biological Data new Thu 14 Apr 2016   09:30 Finished

This two day course will cover network-based approaches to visualise and analyse complex biological ‘big’ data and model pathway systems. The course will be centred on the use of BioLayout Express3D, a tool developed between scientists at the University of Edinburgh and EBI over the last 10 years.

BioLayout provides rapid and versatile means to explore and integrate very large datasets, providing a stunning interface to visualise the relationships between 10’s of thousands of data points. Originally designed for the analysis of microarray data, it is equally effective in analysing data matrices from other analysis platforms.

Day one of the course will introduce principles of network analysis and their use as a generic medium to understand relationships between entities. We will introduce the basics of network visualisation and navigation within BioLayout and principles of correlation analysis of data matrices. We will then explore how data can be explored and clustered within the tool and how you can use the software to rapidly extract meaning from large and complex datasets.

Day two will focus on pathway modelling. We will explain how to collate information about a given system of interest from the literature, and to turn this information into a logic-based pathway model. We will then explore how these models can be parametrised and imported into BioLayout where simulations can be run that model the dynamics of these systems under different conditions. For more information see: http://www.virtuallyimmune.org/

A draft agenda can be found here.

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.

Next Generation Sequencing data analysis Tue 17 Mar 2015   09:00 Finished

This course provides an introduction to next generation sequencing (NGS) data analysis methodologies. Lectures will give insight into how biological knowledge can be generated from RNA-seq, ChIP-seq and DNA-seq experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of RNA-seq, ChIP-seq and DNA-seq data under the guidance of the lecturers and teaching assistants. It is aimed at researchers who are applying or planning to apply NGS technologies and bioinformatics methods in their research.

The timetable for this event can be found here.

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.

  • Nowomics - Access to the latest data and papers relevant to your research
  • Nowomics is a new website to help biologists stay up to date with the latest data and papers relevant to their research. Try it here.
  • Nowomics tracks new papers and many types of data in online repositories. You ‘follow’ the genes and processes you work on to see a Twitter-like news feed of new papers, annotation, interactions, curated comments and more.
  • For each gene you can also include information from orthologues and related genes directly in your news feed.
  • Data are currently included for human, mouse, rat, fly and plant.
  • This short workshop will show you how to use the Beta version of Nowomics to find the latest information for genes & keywords, how to set up your personalised news feed and configure email alerts. We’ll also demonstrate new portals to help researchers working on Drosophila or Arabidopsis find the latest and most popular papers.

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

Ontologies and ontology-based data analysis Wed 21 Nov 2018   10:00 Finished

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 wheelchair or level access available to this level.

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.

Open Targets is a public-private partnership to use human genetics, genomic data and drug information for systematic identification and prioritisation of therapeutic targets. This module introduces the Open Targets partnership, its underlying projects and the bioinformatics resources for researchers studying associations of human genes with diseases.

We offer interactive and hands-on experience with Open Targets Platform and Open Targets Genetics, open source tools of integrated biological and chemical data for drug target identification and prioritisation. We cover user cases relevant to the biomedical and pharmaceutical communities and can customise the course according to specific therapeutic areas.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

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.

Jalview hands-on training course is for anyone who works with sequence data and multiple sequence alignments from proteins, RNA and DNA.

Jalview is free software for protein and nucleic acid sequence alignment generation, visualisation and analysis. It includes sophisticated editing options and provides a range of analysis tools to investigate the structure and function of macromolecules through a multiple window interface. For example, Jalview supports 8 popular methods for multiple sequence alignment, prediction of protein secondary structure by JPred and disorder prediction by four methods. Jalview also has options to generate phylogenetic trees, and assess consensus and conservation across sequence families. Sequences, alignments and additional annotation can be accessed directly from public databases and journal-quality figures generated for publication.

The course involves of a mixture of talks and hands-on exercises.

Day 1 is an introduction to protein multiple sequence alignment editing and analysis with Jalview.

Day 2 focuses on using Jalview for RNA sequence analysis, and also integrating cDNA and protein analysis and covers more advanced applications after lunch.

Day 3 concentrates on protein secondary structure prediction with JPred version 4 as well as protein sub-family analysis to identify functionally important residues.

There will be opportunities for attendees to get advice on analysis of their own sequence families.

Further information, including some training videos, is also available.

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

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