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Cursus: NWI-MOL109
NWI-MOL109
Chemometrics for Molecular Life Sciences
Cursus informatieRooster
CursusNWI-MOL109
Studiepunten (ECTS)6
CategorieBA (Bachelor)
VoertaalEngels
Aangeboden doorRadboud Universiteit; Faculteit der Natuurwetenschappen, Wiskunde en Informatica; Moleculaire Wetenschappen;
Docenten
Coördinator
dr. J.J. Jansen
Overige cursussen docent
Contactpersoon van de cursus
dr. J.J. Jansen
Overige cursussen docent
Docent
dr. J.J. Jansen
Overige cursussen docent
Docent
dr. G.J. Postma
Overige cursussen docent
Collegejaar2016
Periode
KW3  (30-01-2017 t/m 09-04-2017)
Aanvangsblok
KW3
Onderwijsvorm
voltijd
Opmerking-
Inschrijven via OSIRISJa
Inschrijven voor bijvakkersJa
VoorinschrijvingNee
WachtlijstNee
Plaatsingsprocedure-
Cursusdoelen

The goal of the course is that the student learns to apply and familiarize him/herself with the techniques that constitute the cornerstones of modern data analysis. These data visualization and analysis techniques are crucial in e.g. modern molecular life sciences.

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 chemometrical techniques that the student will master are listed under Subjects. 

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 programing skills are required to successfully follow this course.

Inhoud

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.

Visualisation of complex multivariate data is another issue in data analysis. 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.  A short and non-exhaustive list of areas is: metabolomics,  proteomics, genomics, finding biomarkers that are indicative for specific diseases, etcetera. During the course the various chemometrical techniques are studied and exercised thoroughly. The student will learn to conduct the analyses with the most widely used chemometric methods in a validated and robust way. The student will also learn to interpret the resulting models to obtain information for further medical/biological study.

The course is obligatory for students doing a master internship at the Department of Analytical Chemistry.

Bijzonderheden
• This course is a follow up of the data analysis topics in the 'RNA' course NWI-MOL107.
• A follow-up course is Pattern Recognition in the Natural Sciences (SM299).
• The course will be given in parallel with the course Chemometrics (MOL065).
Onderwerpen
• Multivariate analysis, Principal Component Analysis (PCA)
• Clustering techniques (hierarchical, k-means)
• Classification (discriminant analysis, nearest-neighbour methods)
• Multivariate regression (PCR, PLS)
• Validation strategies.
Toetsinformatie
Four assignments: three in pairs of students, forth individual. All grades must be sufficient and the forth assignment counts for 50% in the final grade.
Voorkennis
• Statistics (NWI-MOL028)
• Basic Linear Algebra is beneficial.

This is a course in the theme 'Methods'.
Literatuur

• At the course web site (webchem2.science.ru.nl/chemometrics-MLW/) the students can find a reader, a guide to the computer excercises, and several data sets.
• Massart, Vandeginste et al., Handbook of chemometrics and qualimetrics, parts A (ISBN 0-444-89724-0) and B (ISBN 0-444-82853-2) . These books are available for consultation in the library as well as in the reading room of the Department of Analytical Chemistry.
Werkvormen

• 16 hours guided individual project work
• 16 hours computer course
• 9 hours lecture
• 127 hours individual study period
Verplicht materiaal
Dictaat
At the course web site (webchem2.science.ru.nl/chemometrics-MLW/) the students can find a reader, a guide to the computer excercises, and several data sets.
Aanbevolen materiaal
Boek
Massart, Vandeginste et al., Handbook of chemometrics and qualimetrics, parts A and B. These books are available for consultation in the library as well as in the reading room of the Department of Analytical Chemistry.
Werkvormen
Computerpracticum
AanwezigheidsplichtJa

Hoorcollege
AanwezigheidsplichtJa

Project
AanwezigheidsplichtJa

Zelfstudie
AanwezigheidsplichtJa

Toetsen
Tentamen
Weging1
GelegenhedenBlok KW3, Blok KW4

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