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The course teaches the student to apply and familiarize him/herself with the techniques that constitute the cornerstones of modern Chemical data analysis. These data visualization and analysis techniques are crucial in contemporary biomedicine.
At the end of the course the student:
- ...knows the principles of the most important chemometrical methods;
- ...can select the proper technique, based on the biological/biochemical question;
- ...can apply each technique in the correct context on several real life data sets of different size and complexity;
- ...can correctly interpret and validate the results and can translate them to answers to the biological/biochemical question.
The course is related to the course Chemometrics (MOL065), however in this course (MOL109) the focus will be on the correct application, validation and interpretation of the results, using a user friendly, dedicated data analysis program. No programming skills are required to successfully follow this course.
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During the statistics course, the main focus was on univariate chemical and biological data analysis. However, modern life sciences experiments yield multivariate measurements on chemical and biological systems. Examples are NMR spectra, NIR spectra or mass spectral data. Analysis of such data requires techniques that take the multivariate character of the data into account, providing improved results as compared to simple univariate analysis. This in turn leads to better (disease) understanding or predictions. In general more and better information is obtained from life sciences experiments using multivariate data analysis methods.
This course provides you with the main tools for multivariate data visualization and analysis.
The course gives an overview of the basic chemometric methods, sometimes described as 'Chemical Data Science’, using examples, relevant for molecular life scientists. The methods that will be covered are :
- Exploratory Analysis of multivariate data
- Clustering
- Classification
- Multivariate regression and prediction
The course will focus on methods to handle experiemntal measurements as data, with a focus on the extraction of biomedical information (i.e. biomarkers). The course will treat applications in metabolomics, proteomics and genomics. During the course the various chemometric techniques are studied and exercised thoroughly, with a focus on interpretation of the resulting models in a validated and robust way.
The course is obligatory for students doing a master internship at the Department of Analytical Chemistry.
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