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Research Informatics Training

Research Informatics Training

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Foundational skills

Foundational skills overview Data analysis in Python Data analysis in R Fundamentals of Python Programming Reproducible Research Scientific Figure Design AI Prompting for Biologists

Bioinformatics

Bioinformatics overview Building Computational Pipelines with Nextflow Bulk RNA-seq analysis Expression Proteomics Analysis in R Extracting Biological Information from Gene Lists Foundations of Phylogenetic Inference Introduction to the Unix Command Line Managing Bioinformatics Software and Pipelines Metabolomics Data Analysis Metagenomics Data Analysis Protein Structure Prediction and Analysis Quality Control in Sequencing Experiments Single-cell RNA-seq analysis Spatial Transcriptomics Analysis Working on HPC clusters Working with Bacterial Genomes

Applied Statistics

Applied Statistics overview Bayesian inference Core statistics Experimental design for stats Generalised linear models Linear mixed effects models

Machine Learning

Machine Learning overview Principles of Machine Learning

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Training venues overview Research Informatics Training room eLearning Suite Pembroke Teaching Rooms
Home Events Training People About us
Home Events Training People About us

Events

    Events overview Registration fees Cancellation and Non-attendance Accessibility support Terms and Conditions Waiting list

Training

    Our courses Foundational skills Bioinformatics Applied Statistics Machine Learning Undergraduate Training Bespoke training

People

    Core Team Trainers Alumni

About us

    About us Training venues Visitor information

Research Informatics Training

small sapling in the ground
Foundational skills

Develop the computational and data analysis skills needed to manage, analyse, and interpret datasets using tools such as Python, R, Unix, and HPC.

Applied Statistics
Applied Statistics

Develop practical statistical skills to design experiments, and apply methods such as hypothesis testing, linear models, and Bayesian inference to real-world data.

DNA
Bioinformatics

Develop practical skills for analysing biological datasets using modern bioinformatics methods, including sequencing, genomics, transcriptomics, proteomics, and computational workflows.

Machine Learning
Machine Learning

Learn how to use machine learning to analyse complex datasets, identify patterns, and generate predictions from research data.

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Please review our Events Overview for the extended schedule.

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Research Informatics Training

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University of Cambridge Department of Genetics Downing Street, Cambridge CB2 3EH
Email:bioinfotraining@bio.cam.ac.uk

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