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• • Content provider
  • University of Cambridge Bioinformatics Training2
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• • Keyword
  • HDRUK2
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• • Scientific topic
  • Bioinformatics1
  • Protein bioinformatics1
  • Protein databases1
  • Protein informatics1
  • Proteins1
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• • Event type
  • Workshops and courses2
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• • Venue
  • Craik-Marshall Building2
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• • City
  • Cambridge2
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• • Country
  • United Kingdom2
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• • Target audience
  • This workshop is aimed at researchers who want to learn more about the UniProt resources
  • Institutions and other external Institutions or individuals568
  • Postdocs and Staff members from the University of Cambridge568
  • Graduate students567
  • Everyone is welcome to attend the courses55
  • please review the policies.54
  • as well as other departmental training within the University of Cambridge (potentially under a different name) so participants who have attended statistics training elsewhere should check before applying.28
  • This course is included as part of several DTP and MPhil programmes23
  • <span style="color:#FF0000">After you have booked a place22
  • if you are unable to attend any of the live sessions and would like to work in your own time22
  • including for registered university students.<span style="color:#FF0000">22
  • please email the Team as Attendance will be taken on all courses. A charge is applied for non-attendance22
  • This is aimed at life scientists with little or no experience in machine learning and that are looking at implementing these approaches in their research.16
  • It may be particularly useful for those who have attended other Facility Courses and now need to process their data on a Linux server. It will also benefit those who find themselves using their personal computers to run computationally demanding analysis/simulations and would like to learn how to adapt these to run on a HPC.15
  • This course is aimed at students and researchers of any background.15
  • We assume no prior knowledge of what a HPC is or how to use it.15
  • Existing R users who are not familiar with dplyr and ggplot211
  • Those with programming experience in other languages that want to know what R can offer them11
  • Bioinformaticians and wet-lab biologists who can program10
  • PhD students9
  • Researchers who are applying or planning to apply image analysis in their research7
  • The course is aimed at biologists interested in microbiology7
  • This workshop is aimed at researchers interested in proteins7
  • network analysis7
  • Researchers6
  • The course is aimed primarily at mid-career scientists – especially those whose formal education likely included statistics6
  • but who have not perhaps put this into practice since.6
  • protein-protein interactions and related areas6
  • Biologists and bioinformaticians5
  • Note that we will not cover specific topics in phylogenomics (whole-genome phylogenies) or bacterial genomics.5
  • The course is open to Graduate students5
  • This course is - in abbreviated form - included as part of several DTP and MPhil programmes5
  • This course is aimed at researchers with no prior experience in phylogenetic analysis who would like an introduction to the foundations of building phylogenies from relatively small sequences (viral genomes and/or targeted regions of eukaryotic genomes).5
  • but not essential as we will walk through a MS typical experiment and data as part of learning about the tools.5
  • post-docs5
  • Anyone who is using sequencing as part of their work and/or research.4
  • Biologists4
  • Familiarity with mass spectrometry or proteomics in general is desirable4
  • Novice users of HPC and anyone who expects to need to use HPC systems at some stage in their research4
  • Researchers who want to extract quantitative information from microscopy images4
  • The course is targeted to either proteomics practitioners or data analysts/bioinformaticians that would like to learn how to use R to analyse proteomics data.4
  • This course is aimed at researchers with an interest in metabolomics and its applications4
  • This workshop is aimed at researchers who need to undertake sequence searching as part of their work4
  • bioinformatics and other life scientists planning to work with next-generation sequencing data.4
  • or who need to search against several biological datasets to gain knowledge of a gene/gene set4
  • prokaryotic genomics and antimicrobial resistance.4
  • wet-lab scientists4
  • <span style="color:#FF0000">There is no fee charged for this event''<span style="color:#FF0000">.3
  • Graduates, postgraduates, and PIs, who are using, or planning to use, RNA-seq technology in their research and want to learn how to process and analyse RNA-seq data.3
  • Graduates, postgraduates, and PIs, who are using, or planning to use, the statistical software R to manipulate and analyse NGS and other data in their research. This is an introductory level course: no prior experience of R is necessary before starting the workshop.3
  • Graduates, postgraduates, and PIs, without any previous command-line experience, who want to learn to use the Linux command-line in order to be able to work with large data files.3
  • Institutions and other external Institutions or individuals.3
  • Institutions and other external institutions or individuals.3
  • No prior experience in the analysis of these types of data is required.3
  • Postdocs and other Research Staff from the University of Cambridge3
  • The course is aimed at <b>bench biologists and bioinformaticians</b> who need to analyse their own data against large biological datasets3
  • The course is aimed at people at postgraduate level who are involved in research.3
  • The course is open to Postdocs and Staff members from the University of Cambridge3
  • The module is suitable for researchers interested in gene expression analysis and visualisation3
  • The workshop is aimed to biologists or computer scientists with little or no previous knowledge of Cytoscape3
  • This course is aimed at researchers with an interest in metabolomics and its applications.3
  • This introductory course is aimed at biologists with little or no experience in machine learning.3
  • This workshop is aimed at students on the Rare Diseases and Experimental Medicine MPhil courses at the University of Cambridge. Students from the wider clinical sciences group are also able to attend subject to space being available.3
  • Undergraduate students3
  • analysis of complex microbiomes and antimicrobial resistance.3
  • bioinformaticians3
  • pathways and diseases.3
  • prokaryotic genomics3
  • <span style="color:#0000FF"> Non-members of the University of Cambridge to pay £575 </span style>2
  • <span style="color:#0000FF">All Members of the University of Cambridge to pay £250 </span style> <span style="color:#FF0000">A booking will only be approved and confirmed once the fee has been paid in full.</span style>2
  • <span style="color:#FF0000">There is no fee charged for this event''<span style="color:#FF0000">2
  • Anyone wanting to use OMERO to organize2
  • Applicants are expected to have a working knowledge of R.2
  • Biological sciences research students and postdocs who may want to use HPC in their research. Please note that Biochemistry first year graduate students book this course via their Moodle site not here.2
  • Cytoscape will have to be downloaded and installed on your device for the practical sessions.2
  • Facility Managers wanting to train users2
  • Further details regarding eligibility criteria are available here2
  • Graduates, postgraduates, and PIs, who are using, or planning to use, single cell RNA-seq technology in their research and want to learn how to process and analyse single cell RNA-seq data.2
  • Guidance on visiting Cambridge and finding accommodation is available here. <div class="heading">Bookings and fees</div> Please note that all participants attending this course will be charged a <b>registration fee</b>. The fees are as follows:2
  • Institutions and other external Institutions2
  • Operators, developers and managers of bioinformatics resources2
  • Part of CRUK Bioinformatics Summer School:Unix and R Foundations 20222
  • Participants organised through CRUK Cambridge Centre2
  • PhD Students2
  • Please review the policies.2
  • Principal Investigators from the University of Cambridge2
  • Students and researchers from life-sciences or biomedical backgrounds2
  • Suitable for students and early career researchers2
  • The course is recommended for all staff and students who use Linux in their research or plan on attending the CI High Performance Computing facilities (Cluster) course.2
  • The workshop is suitable for scientists that are producing sequence data and require a platform to publish it2
  • This course is aimed at researchers with no prior experience in the analysis of ChIP-seq data2
  • This course is for researchers from a broad biological background as the techniques learned can be applied to any InterMine database2
  • This course is intended for researchers who need to analyse genomic data in order to call genomic variants. Aside from a basic understanding of molecular biology, attendees must have a working knowledge of how to use the Linux BASH command line; our 1-day 'Linux for bioinformatics' course is a suitable background.2
  • This tutorial is basic and requires no prior knowledge of any coding language or software.2
  • This webinar is suitable for students and early career researchers with interest in Genomics2
  • This workshop is aimed at researchers who are either generating or integrating molecular interaction data in their research. This could be protein-protein interaction as well as protein-RNA2
  • This workshop is aimed at researchers who are looking for an overview of the bioinformatics resources provided by EMBL-EBI2
  • This workshop is aimed at researchers who want to learn about pathways or identify pathways relevant to a set of molecules2
  • This workshop is aimed at researchers who wish to understand why data standards are important and how they can be used in practice2
  • This workshop is aimed at researchers who wish to use and submit functional genomics data. This workshop will not however cover the analysis of such data.2
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