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  • University of Cambridge Bioinformatics Training8
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• • Keyword
  • HDRUK8
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• • Scientific topic
  • Data visualisation
  • Aerobiology8
  • Behavioural biology8
  • Bioinformatics8
  • Biological rhythms8
  • Biological science8
  • Biology8
  • Chronobiology8
  • Cryobiology8
  • Data rendering8
  • Reproductive biology8
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• • Event type
  • Workshops and courses8
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• • Venue
  • Craik-Marshall Building8
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  • Cambridge8
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  • United Kingdom8
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• • Target audience
  • Existing R users who are not familiar with dplyr and ggplot2
  • Postdocs and Staff members from the University of Cambridge102
  • Institutions and other external Institutions or individuals101
  • Graduate students99
  • Those with programming experience in other languages that want to know what R can offer them8
  • 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
  • Researchers who are applying or planning to apply image analysis in their research4
  • Researchers who want to extract quantitative information from microscopy images4
  • This course is aimed at researchers with an interest in metabolomics and its applications4
  • Plant research3
  • The course is open to Graduate students3
  • <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
  • pathways and diseases.2
  • <span style="color:#FF0000">Please note that all participants attending this course will be charged a registration fee.1
  • <span style="color:#FF0000">Please note that all participants attending this course will be charged a registration fee. <span style="color:#0000FF"> Members of Industry to pay 575.00 GBP. </span style> <span style="color:#0000FF">All Members of the University of Cambridge1
  • <span style="color:#FF0000">There is no fee charged for this event''<span style="color:#FF0000">.1
  • Affiliated Institutions and other academic participants from External Institutions and Charitable Organizations to pay 250.00 GBP. </span style> <span style="color:#FF0000">A booking will only be approved and confirmed once the fee has been paid in full.</span style>1
  • Applicants are expected to have an interest in learning about bioinformatics and/or are in the beginning stages of using bioinformatics in their research with the need to develop their skills and knowledge further.1
  • BioImage Analysts with some experience of basic microscopy image analysis1
  • Bioinformaticians1
  • Bioinformaticians and Biologists who want to learn how to manipulate, process data, and make plots using R1
  • Biologists1
  • Biophysicists1
  • Cell Biologists1
  • Day1 is intended for biologists and computer scientists interested in using LithoGraphX. Some experience in imaging is desirable but not required.1
  • Day2 is intended for computer scientists wanting either to write their own algorithm or automate complex protocols. Basic python knowledge and familiar with C++ are required.1
  • Experimental Researchers1
  • Graduate Students1
  • Institutions and other external Institutions or individuals.1
  • Life Science Researchers1
  • Master students1
  • No previous knowledge of programming is required for this course.1
  • People from any area with little or no prior computational experience1
  • PhD students1
  • Research presentation1
  • Researchers1
  • The course is aimed at biologists interested in microbiology1
  • 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. Familiarity with mass spectrometry or proteomics in general is desirable1
  • The hands­on component is aimed at novice to intermediate users who are seeking detailed guidance with GATK and related tools.1
  • The lecture­ based component of the workshop is aimed at a mixed audience of people who are new to the topic of variant discovery or to GATK1
  • This course is aimed at individuals working across biological and biomedical sciences who have little or no experience in bioinformatics.1
  • This course is aimed at individuals working across biological and biomedical sciences who have little to no experience in bioinformatics.1
  • This course is appropriate for researchers who are relatively proficient with computers but maybe not had the time or resources available to become programmers.1
  • This course is suitable for all users who have an interest in biomedical research and therapeutics. A special emphasis will be given on drug discovery and target validation. It will also be useful to those who seek for practical examples on how large-scale genomic experiments and computational techniques are integrated and visualised in a web platform.1
  • This course is suitable for anyone who has an interest in biomedical and therapeutic research with a special emphasis on target identification and prioritisation1
  • This course is suitable for anyone who has an interest in biomedical research and therapeutics with a special emphasis on drug discovery and target validation. It is also useful to those who wish to find out how large-scale genomic experiments1
  • This course may be of interest to physical scientists looking to develop their knowledge of Python coding in the context of bioimage analysis1
  • This hands-on event is suitable for anyone who has an interest in building data science workflows with different kinds of life science data.1
  • This webinar is suitable for students and early career researchers in the Life Sciences.1
  • analysis of complex microbiomes and antimicrobial resistance.1
  • but not essential as we will walk through a MS typical experiment and data as part of learning about the tools.1
  • cellular models of disease and computational techniques are used to identify and validate the causal links between targets1
  • computational and statistical techniques are used to identify and validate the causal links between targets1
  • early stages of drug discovery. It is also useful to those who wish to find out how large-scale genomic experiments1
  • or who are already GATK users seeking to improve their understanding of and proficiency with the tools.1
  • postdocs1
  • prokaryotic genomics1
  • seeking an introductory course into the tools1
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  • United Kingdom8
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