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All Bioinformatics courses

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Big Data and Cloud Computing new Fri 1 Jun 2018   09:30 Finished

Recent advances in genomics, proteomics, imaging and other technologies, have resulted in data being generated at a faster rate than they can be meaningfully analysed. In this course we will show you how cloud computing can be used to meet the challenges of storage, management and analysis of big data. The first half of the course will introduce cloud infrastructure technologies. The second half will cover tools for collaborative working, resource management, and creation of workflows. The instructors will demonstrate how they are using cloud computing in their own research.

N.B. If you sign up for this course, you will be automatically registered for an AWS educate account, which will provide you with sufficient AWS credits to complete the course exercises. If you decide to continue using cloud computing after the course, you will need to either purchase more credits or apply for a grant from programs like: AWS Cloud Credits for Research, Microsoft Azure for Research or Google Cloud Platform Education Grants.

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

In this course we will introduce web-based, open source tools to analyse and interpret high-throughput biological data.

The main focus will be g:Profiler - a toolset for finding most significant functional groups for a given gene or protein list; MEM - a query engine allowing to mine hundreds of public gene expression datasets to find most co-expressed genes based on a query gene; and ClustVis - a web tool for visualizing clustering of multivariate data using Principal Component Analysis (PCA) plot and heatmap.

MEM and g:Profiler are ELIXIR-Estonia node services.

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

Bioinformatics for Principal Investigators Mon 16 Sep 2019   09:30 Finished

The aim of this workshop is to provide principal investigators with an introduction to the challenges of working with biological data and to the best practices, and tools, needed to perform bioinformatics research effectively and reproducibly.

On day 1, we will cover the importance of experimental design, discuss the challenges associated with (i) the analysis of high-throughput sequencing data (utilising RNA-seq as a working example) and (ii) the application of machine learning algorithms, as well as issues relating to reusability and reproducibility.

On day 2, we will put into practice concepts from day 1, running a RNA-seq data analysis pipeline, going from raw reads through differential expression analysis and the interpretation of downstream analysis results. Challenges encountered at each step of the analytical pipeline will be discussed. Please note that day 2 is optional.

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.

InterMine is a freely available data integration and analysis system that has been used to create a suite of databases for the analysis of large and complex biological data sets.

InterMine-based data analysis platforms are available for many organisms including mouse, rat, budding yeast, plants, nematodes, fly, zebrafish and more recently human. See here for a comprehensive list of InterMine databases.

The InterMine web interface offers sophisticated query and visualisation tools, as well as comprehensive web services for bioinformaticians. Genomic and proteomic data within InterMine databases includes pathways, gene expression, interactions, sequence variants, GWAS, regulatory data and protein expression.

This course will focus on the InterMine web interface and will introduce participants to all aspects of the user interface, starting with some simple exercises and building up to more complex analysis encompassing several analysis tools and comparative analysis across organisms. The exercises will mainly use the fly, human and mouse databases, but the course is applicable to anyone working with data for which an InterMine database is available.

This event is organised alongside a half day course on Biological data analysis using the InterMine API. More information on this event are available 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 Interest by linking here.

Biological data analysis using the InterMine API new Wed 19 Jun 2019   13:30 Finished

InterMine is a freely available data integration and analysis system that has been used to create a suite of databases for the analysis of large and complex biological data sets.

InterMine-based data analysis platforms are available for many organisms including mouse, rat, budding yeast, plants, nematodes, fly, zebrafish and more recently human. See here for a comprehensive list of InterMine databases. Genomic and proteomic data within InterMine databases includes pathways, gene expression, interactions, sequence variants, GWAS, regulatory data and protein expression.

InterMine provides sophisticated query and visualisation tools both through a web interface and an extensive API; this course will focus on programmatic access to InterMine through its API and on running InterMine searches using Python, Perl and R scripts. The exercises will mainly use the fly, human and mouse databases, but the course is applicable to anyone working with data for which an InterMine database is available.

This event is organised alongside a half day course on Biological data analysis using the InterMine User Interface. More information on this event are available 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 Interest by linking here.

The Open Microscopy Environment (OME) is an open-source software project that develops tools that enable access, analysis, visualization, sharing and publication of biological image data.

OME has three components:

  • OME-TIFF, standardised file format and data model;
  • Bio-Formats, a software library for reading proprietary image file formats; and
  • OMERO, a software platform for image data management and analysis.

In this one day course, we will present the OMERO platform, and show how Facility Managers can use it to manage users, groups, and their microscopy, HCS and digital pathology data.

Help pages on 'Using OMERO for Facility Managers' can be found here.

This course is organized alongside a one day course on Biological Imaging Data Management for Life Scientists. More information on this event are available here.

This course will be delivered by members of the OMERO team. The OME project is supported by BBSRC and Wellcome Trust.

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.

The Open Microscopy Environment (OME) is an open-source software project that develops tools that enable access, analysis, visualization, sharing and publication of biological image data.

OME has three components:

  • OME-TIFF, standardised file format and data model;
  • Bio-Formats, a software library for reading proprietary image file formats; and
  • OMERO, a software platform for image data management and analysis.

In this one day course, we will present the OMERO platform, and show how to import, organise, view, search, annotate and publish imaging data. Additionally, we will briefly introduce how to use a variety of processing tools with OMERO.

This course is organized alongside a one day course on Biological Imaging Data Processing for Data Scientists. More information on this event are available here.

This course will be delivered by members of the OMERO team. The OME project is supported by BBSRC and Wellcome Trust.

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.

The Open Microscopy Environment (OME) is an open-source software project that develops tools that enable access, analysis, visualization, sharing and publication of biological image data.

OME has three components:

  • OME-TIFF, standardised file format and data model;
  • Bio-Formats, a software library for reading proprietary image file formats; and
  • OMERO, a software platform for image data management and analysis.

In this one day course, we will present the OMERO platform, and show how to transition from manual data processing to automated processing workflows. We will introduce how to write applications against the OMERO API, how to integrate a variety of processing tools with OMERO and how to automatically generate output ready for publication.

This course is organized alongside a one day course on Biological Imaging Data Management for Life Scientists. More information on this event are available here.

This course will be delivered by members of the OMERO team. The OME project is supported by BBSRC and Wellcome Trust.

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.

ChIP-seq and ATAC-seq analysis Wed 23 Oct 2019   09:30 Finished

The primary aim of this course is to familiarise participants with the analysis of ChIP-seq and ATAC-seq data and provide hands-on training on the latest analytical approaches.

The course starts with an introduction to ChIP-seq experiments for the detection of genome-wide DNA binding sites of transcription factors and other proteins. We first show data quality control and basic analytical steps such as alignment, peak calling and motif analysis, followed by practical examples on how to work with biological replicates and fundamental quality metrics for ChIP-seq datasets. On the second day, we then focus on the analysis of differential binding, comparing between different samples. We will also give an introduction to ATAC-seq data analysis for the detection of regions of open chromatin.

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.

COSMIC, the Catalogue of Somatic Mutations in Cancer, is the world’s largest and most comprehensive expert manually curated resource for exploring the impact of somatic mutations in human cancer. Based at the Wellcome Sanger Institute and available publicly at https://cancer.sanger.ac.uk/cosmic, the latest release includes almost 6 million coding mutations across 1.4 million samples from over 26,000 papers. COSMIC captures the full spectrum of genomic data relating to somatic mutations, so in addition to coding mutations, gene fusions, non-coding mutations, copy-number variants, methylation and drug resistance mutations are included.

This course will use the live COSMIC website and tools to show you how to access and explore this information, seeking to identify genetic causes and targets in all human cancers.

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.

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