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https://github.com/lskatz/awesome-bioinformatics-education

resources for bioinformatics education
https://github.com/lskatz/awesome-bioinformatics-education

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resources for bioinformatics education

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README 

        

# Awesome Bioinformatics Education [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)



A curated list of resources specific to learning bioinformatics.

I appreciate any help! For contributing, please see [CONTRIBUTING.md](CONTRIBUTING.md).



## Contents



* [Full courses](#full-courses)

* [Hands on](#hands-on)

* [Specific tools or topics](#specific-tools-or-topics)

* [Further reading](#further-reading)

* [Uncategorized](#uncategorized)



## Full courses



### Full accredited courses



Places where you can directly earn a certificate or where real students are earning real credits



* MIT Open Courseware

  * [Computational biology](https://ocw.mit.edu/courses/6-047-computational-biology-fall-2015/)

  * [Bioinformatics and Proteomics](https://ocw.mit.edu/courses/6-092-bioinformatics-and-proteomics-january-iap-2005/)

  * [Foundations of Computational and Systems Biology](https://ocw.mit.edu/courses/7-91j-foundations-of-computational-and-systems-biology-spring-2014/)

* [Applied Computational Genomics Course at UU: Sprint 2022](https://github.com/quinlan-lab/applied-computational-genomics)

* [HarvardX Biomedical Data Science Open Online Training](https://rafalab.github.io/pages/harvardx.html)

* [Titus Brown's class materials](https://github.com/ngs-docs)

* [Meren Lab's tutorials (central tab)](https://merenlab.org/2015/07/20/analyzing-variability/ )

* [Astrobio Mike's tutorials](https://astrobiomike.github.io/all_tutorials/)

* [Ben Langmead's teaching materials](http://www.langmead-lab.org/teaching-materials/)

* [SciLifeLab course listings](https://scilifelab.github.io/courses/)

* [Andrea Telatin's tutorials](https://telatin.github.io/microbiome-bioinformatics/ )

* [Free code camp](https://www.freecodecamp.org/)

* [DataCamp](https://www.datacamp.com/)

* [Udemy](https://www.udemy.com/)

* Coursera

  * [Python Basics](https://www.coursera.org/learn/python-basics)

  * [Data Structures](https://www.coursera.org/learn/python-functions-files-dictionaries?specialization=python-3-programming#syllabus)

  * [Object Oriented Programming](https://www.coursera.org/learn/python-classes-inheritance)

* [Bioinformatics Workbook](https://bioinformaticsworkbook.org/list.html#gsc.tab=0) - Takes you from unix basics and the HPC all the way through advanced concepts. These concepts include computational like `bioawk` and containers, project management like GitHub and Slack, and all sorts of bioinformatics topics.

  

### Full unaccredited courses



* [Pathogen genomics data analysis course - Conor Meehan](https://conmeehan.github.io/PathogenDataCourse/PathogenCourse.html)

* [MMB DTP Training](https://mmbdtp.github.io/) - A problem-based learning curriculum for the "Microbes, Microbiomes and Bioinformatics" doctoral training program.

* [Computational Genomics and Bioinformatics Class](https://linsalrob.github.io/ComputationalGenomicsManual/)

* [Pathogen Bioinformatics Workshop held at SANBI](https://pabix.sanbi.ac.za/)

* [Bioinformatics for Genomic Epidemiology - SANBI March 2024](https://pathogen-genomics-march-2024.sanbi.ac.za/)

* [WCS AMR Africa 24 - NICD March 2024](https://github.com/WCSCourses/AMR-Africa-24/tree/main)



## Hands on



* [Rosalind](https://rosalind.info)



## Specific tools or topics



* [Perfect bacterial genome tutorial](https://github.com/rrwick/Perfect-bacterial-genome-tutorial)

* [Tools for RNAseq Analyses](https://hobrien.github.io/RNAseqTools/)

* [Hi-C with Chromosomal Conformation Course](https://github.com/4DGenome/Chromosomal-Conformation-Course)

* [GWAS Tutorial](https://github.com/agolotin/BIO465Tutorial)

* [Analysis of single cell RNA-seq data course](https://github.com/hemberg-lab/scRNA.seq.course)

* [Metagenome annotation workflow for UBC's MICB405 Microbial Bioinformatics course](https://github.com/cmorganl/MICB405-Metagenomics)

* [Workshop in microbial metagenome analysis at Michigan State University](https://github.com/edamame-course)

* [Statistics training from Quadram Institute](https://georgemsavva.github.io/R_for_Statistics/index.html )

* [Taming the BEAST (molecular clock analysis)](https://taming-the-beast.org/)



### Phylogenetics or phylogenomics



* [Tutorials on phylogenetic and phylogenomic inference](https://github.com/mmatschiner/tutorials)

* [Genomic epidemiology workshops from bioinformatics.ca](https://bioinformatics.ca/workshops/previous-workshops/)

  * [Genomic epidemiology workshop 2023](https://bioinformatics.ca/workshops-all/2023-infectious-disease-genomic-epidemiology/)

  * [Genomic epidemiology workshop 2021](https://bioinformaticsdotca.github.io/IDE_2021)  



### Galaxy



Galaxy is a very large but specific tool with lots of different possible tutorials, e.g.:



* [Galaxy Training: Genome Assembly of MRSA using MinION Data](https://training.galaxyproject.org/training-material/topics/assembly/tutorials/mrsa-nanopore/tutorial.html)

* [One-health tag on Galaxy Training Site - Pathogen Bioinformatics](https://training.galaxyproject.org/training-material/search2?query=one-health)

* [Galaxy-wide Tutorial Site](https://training.galaxyproject.org/)

* [Repository of ~140 hours of Galaxy Lectures+Tutorials](https://gallantries.github.io/video-library/library) - under CC-BY license that can be embedded into your [Blackboard/Moodle/etc.](https://gallantries.github.io/video-library/videos/galaxy-interface/ncbi-sarf/slides/) (see button at bottom)



Courses:



* [Smörgåsbord 2021 (Global Galaxy Course)](https://shiltemann.github.io/global-galaxy-course/workshop)

* [Smörgåsbord 2022 (Tapas)](https://gallantries.github.io/video-library/events/smorgasbord2/tapas.html)

* [Smörgåsbord 2023](https://gallantries.github.io/video-library/events/smorgasbord3/)

* [Genomic data analysis](https://speakerdeck.com/jxtx/teaching-genomic-data-analysis-with-galaxy)



Domain Specific Galaxy Servers



* [Metagenomics](https://metagenomics.usegalaxy.eu)

* [Genome Annotation](https://annotation.usegalaxy.eu)

* [Full List](https://galaxyproject.org/use/)



### LLMs



(Help wanted)



Large Language Models (LLMs) include things like

[ChatGPT](https://chat.openai.com/),

[Bing](https://www.microsoft.com/en-us/bing/apis/llm),

[LLAMA](https://research.facebook.com/publications/llama-open-and-efficient-foundation-language-models/),

and

[Bard](https://bard.google.com/).



### Genomic epidemiology



* [Book: An applied genomic epidemiological handbook](https://alliblk.github.io/genepi-book/ )

* [Book: R for applied epidemiology and public health](https://epirhandbook.com/en/)

* [Centre for Genomic Pathogen Surveillance digital epidemiology workshop](https://cgps-group.github.io/digitalepiworkshop/) - Really nice integrated exercises, using EpiCollect, DataFlo, PathogenWatch, Microreact.



### Statistics



* [Book: Modern Statistics for Modern Biology](http://web.stanford.edu/class/bios221/book/index.html )

* [Choosing the correct statistical test in SAS, STATA, SPSS, and R](https://stats.oarc.ucla.edu/other/mult-pkg/whatstat/)



## Further reading



* [Integrating Molecular Biology and Bioinformatics Education](https://www.degruyter.com/document/doi/10.1515/jib-2019-0005/html)



## Uncategorized



I appreciate any help categorizing these!



* [Glittr](https://glittr.org/?per_page=25&sort_by=stargazers&sort_direction=desc) - Git repositories with bioinformatics training material.

* [5-day OUCRU-MORU bioinformatics fundamentals workshop](https://flashton2003.github.io/OUCRU_bioinformatics_training/index.html)

* [List of genome visualisation tools](https://cmdcolin.github.io/awesome-genome-visualization/?latest=true)

* [List of training materials at SIB](https://github.com/sib-swiss/training-collection)

* [List of training materials at GitHub.com/crazyhottommy](https://github.com/crazyhottommy/getting-started-with-genomics-tools-and-resources )

* [Book: Fundamentals of Data Visualization](https://clauswilke.com/dataviz/ )

* [Book: Computational Genomics with R](https://compgenomr.github.io/book/ )

* [Data science in Python - course materials](https://github.com/pycam/python-data-science)

* [CS229: Machine Learning course](http://cs229.stanford.edu/ )

* [Version Control with Git](https://swcarpentry.github.io/git-novice/index.html )

* [Version Control using Git and GitHub](https://docs.github.com/en )