16-18 february 2026
The course will be held in English and will be online.
Lesson timetable:
9 am-1 pm
plan
1) Introduction to Statistical Analysis in Computational Biology
– Types of statistical analysis and data-driven choice of analysis
– Basics of Frequentist statistics for Biology
– Basics of Bayesian statistics for Biology
2) From Statistics to Machine Learning
– Differences between statistical and Machine Learning approaches for Biology
– Introduction to supervised and unsupervised Machine Learning for Biology
– Coding a linear Machine Learning model from scratch in R
– K-means clustering and Gaussian Mixture Model (GMM) from scratch in R and Python
3) From linear Machine Learning to Artificial Neural Networks
– Introduction to artificial neural networks and applications to Biology
– Gradient descent from scratch coding in R and Python
– Neural network from scratch coding in R and Python
– Forward and backward propagation, learning rate, activation functional
4) Decision tree based Machine Learning and Random Forests
– Gini index
– Computing optimal split
– Decision tree from scratch in R
– Ensemble learning and features importances
5) Applications of Artificial Neural Networks to Computational Biology projects
– Deep Learning for Single Cell Biology
– Deep Learning for multiOmics data integration
– Deep Learning for Genomics and Metagenomics
– Deep Learning for Microscopy Imaging
– Deep Learning for clinical diagnostics
DOCENTE:
Nikolay Oskolkov – Metabolic Research Group, Latvian Institute of
Organic Synthesis, Riga, Latvia
Education and Career
- 2016-2025 NBIS SciLifeLab, Lund University, Biology department, Sweden, Senior Bioinformatician
- 2012-2016 Clinic Research Centre, Lund University Diabetes Centre, Department of Clinical Sciences, Sweden, Associate Researcher
- 2010-2011 DTU Nanotech, Technical University of Denmark, Denmark, Postdoctoral Fellow
- 2009-2010 Chemistry Department, University of North Carolina, USA, Postdoctoral Fellow
- 2007-2009 Physical Chemistry Department, University of Lund, Sweden, Postdoctoral Fellow
- 2004-2007 Moscow State University, Russia, and University of Ulm, Germany, PhD in Theoretical Physics
Achievements
>50 scientific articles (24% first author, 10% last author, and 10% corresponding author), h-index: 23, i10-index: 35, 3839 citations, >80 oral and invited talks at scientific conferences
cost of the course
- € 230 + VAT before 20 january 2026
- € 330 + VAT after 20 january 2026
how to participate
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