Training materials
Contributors: Anna Syme or Celia van Gelder or Kaivan Kamali or Lieven Clement or Michael Krone or Pavel Dvorak or Prof. Marc Streit or Prof. Tom Freeman
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hands-on tutorial
Deep Learning (Part 1) - Feedforward neural networks (FNN)
• beginnerStatistics and probability Statistics and machine learning -
hands-on tutorial
Deep Learning (Part 3) - Convolutional neural networks (CNN)
• beginnerStatistics and probability Statistics and machine learning -
slides
Image classification in Galaxy with fruit 360 dataset
• beginnerStatistics and probability Statistics and machine learning -
slides
Convolutional neural networks (CNN) Deep Learning - Part 3
• beginnerStatistics and probability Statistics and machine learning -
slides
Feedforward neural networks (FNN) Deep Learning - Part 1
• beginnerStatistics and probability Statistics and machine learning -
PSLS22 Practical Statistics for the Life Sciences
•• intermediate -
Documentation, Exercise, Handout, Scripts
PDA19 - Proteomics Data Analysis (2019)
•• intermediateProteomics Biological databases Mass spectrometry data -
Documentation, Exercise, Handout, Scripts
PDA18 - Proteomics Data Analysis (2018)
•• intermediateProteomics Biological databases Mass spectrometry data -
Documentation, Exercise, Handout, Scripts
PSLS20 - Practical Statistics for the Life Sciences (2020)
•• intermediateStatistics General Linear Models -
Bioinformatics Summer School 2019
•• intermediateProteomics RNA-Seq Omics Statistics and probability Data handling