Long-standing experience in bioinformatical and biostatistical analysis, DNA analysis, optimisation of specific methods of operating a molecular-genetic laboratory and operating of highly specialised equipment allow us to share our knowledge with those interested in this particular field of medicine.

Our consultancy is most often appreciated by collections of young workplaces starting with bioinformatics or research teams working in different fields. However, we are approached also by experienced organisations and teams wishing to obtain standardised and routine application-ready methods.



Head of courses: Mgr. Juraj Gazdarica, Mgr. Rastislav Hekel


Basic statistical data evaluation

  1. Descriptive characteristics and work with them – mean, median, variance, standard deviation, covariance, correlation
  2. Statistical graphs and their interpretation – boxplot, histogram, column charts

Basic data modeling and advanced statistical testing

  1. Probability distributions – discrete and continuous; testing of one-dimensional data; testing of multidimensional data; normality testing of the data
  2. Linear model – calculation of linear model parameters, interpretation and utilization

Introduction to machine learning

  1. Theory, learning with a teacher, without a teacher, empowering, overestimating and underestimating
  2. Work with numpy, pandas, matplotlib and scikit-leart
  3. Analyzing and preparing data for model training
  4. Selecting a suitable model
  5. Model evaluation and visualization


Fundamentals of sequencing

Head of courses: Mgr. Ján Radvanszky, PhD., Mgr. Lucia Strieskova, PhD.


Theoretical introduction to sequencing

  1. Theoretical course consisting of lectures

Advanced course of first and second generation sequencing

  1. More day course – duration as required by the customer; depends mainly on the required depth and extent of the course
  2. Part of the advanced course is a 1 day theoretical introduction and the remaining days of practical exercises



Head of courses: Mgr. Rastislav Hekel, Mgr. Werner Krampl, Mgr. Miroslav Böhmer


Linux and basic bioinformatics tools

  1. System philosophy, login, permissions, basic file operations, installing tools
  2. Demonstration of the use of console bioinformatics tools for quality control

Introduction to programming

  1. Python Language, Developer Environment, IDLE / Pycharm / Jupyter
  2. Strings, files
  3. Cycles, conditions, functions
  4. Fields, tables

Processing of genomic, transcriptomic and metagenomic data

  1. Genomic assembly from NGS reading, mapping, homologous sequence search, genes identification and annotation
  2. RNA-Seq differential analysis, microbiome composition, quality control, and interpretation of outputs

Statistical evaluation of NGS analysis results

  1. Technical interpretation of NGS analysis results, selection of appropriate statistical tests to determine the significance of hypotheses, graphical visualization of outputs


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