Bioinformatics Tools & Tricks: Hands-On Tutorial for Biologists
Do you want to learn how to analyze your data using free tools and web resources? Do you want to try machine learning, artificial intelligence and predictive modelling? We will show you how to accomplish these and many other common analysis tasks within minutes, using popular free bioinformatics and statistical software.
Each hands-on tutorial will present a sequence of analysis steps: from choosing the right tools, to analyzing the data, to making publication-quality figures. We will pay particular attention to common pitfalls in using bioinformatics software and web resources.
No prior knowledge of computer programming, statistics or machine learning is required – all necessary concepts will be introduced during the tutorial.
Schedule – Fall 2023
|Tue Sep 12||12:00 – 1:00 PM||Introduction to R programming|
|Tue Sep 19||12:00 – 1:00 PM||Exploratory data analysis in R|
|Mon Sep 25||12:00 – 1:00 PM||Data visualization in R|
|Tue Oct 3||12:00 – 1:00 PM||Introduction to Next-Generation Sequencing|
|Tue Oct 10||12:00 – 1:00 PM||RNAseq: bulk and single-cell analysis in R|
|Tue Oct 17||12:00 – 1:00 PM||Genomic variant interpretation using Seqr|
|Tue Oct 24||12:00 – 1:00 PM||Data analysis reproducibility using Git|
|Tue Oct 31||12:00 – 1:00 PM||High-Performance Computing (HPC) – how to use it in research|
|Tue Nov 7||12:00 – 1:00 PM||Introduction to Python programming|
|Tue Nov 14||12:00 – 1:00 PM||Jupyter Notebooks – An introduction to using Python on the HPC|
|Tue Nov 21||12:00 – 1:00 PM||Biomedical data wrangling with Python and Pandas|
|Tue Nov 28||12:00 – 1:00 PM||Introduction to machine learning and AI|
|Tue Dec 5||12:00 – 1:00 PM||Introduction to deep learning and AI in Python|
For registration and more information, please contact Andrei Turinsky (firstname.lastname@example.org).