27411 Biological data analysis and chemometrics
|Biologisk dataanalyse og kemometri|
Point( ECTS )
Taught under single-course student
|Technological specialization course, MSc. Eng., Mathematical Modelling and Computing |
|F2A (Mon 13-17)
Scope and form:
|Lectures, PC work (multivariate statistical
Duration of Course:
Type of assessment:
Not applicable together with:
|Minimum 15 Maximum: 40|
General course objectives:
After the course you will have experience in the common chemometric
methods that are used in all biological and chemical disciplines,
in which advanced spectrometric and analytical separation
techniques are used. Chemometrics is used more and more in basic
science and in the industries.
A student who has met the objectives of the course will be able to:
- Give an overview of important chemometric methods.
- Identify situations where exploratory data-analysis is
- Describe and use the different forms of scaling, transformation
- Understand and describe the difference between classification
- Understand and describe the difference between clustering and
- Apply and interpret principal component analysis (PCA) on
- Apply and interpret the principles of validation and outlier
- Use and interpret cluster analysis on multivariate data.
- Describe, apply and interpret multiple linear regression (MLR)
and ridge regression (RR) and where to apply them in two data
- Describe, apply and interpret principal component regression
(PCR) and partial least squares regression (PLSR) and where to
apply them in two data matrix problems.
- Apply and interpret correspondence analysis.
- Describe the method metric multidimensional
Multivariate statistical treatment of quantitative and qualitative
datamatrices. Exploratory dataanalysis, regression and
classification methods. Scaling and standardization of raw data,
cluster analysis and ordination (eigen value analysis). Principal
component analysis, principal component regression, partial least
square and ridge regression, principal coordinate analysis and
correspondence analysis. Validation of data, especially
cross-validation and jack-knifing. Use of plots in the evaluation
of data. Special problems concerning chemical and biotechnogical
Green challenge participation:
Please contact the teacher for information on whether this course
gives the student the opportunity to prepare a project that may
participate in DTU´s Study Conference on sustainability, climate
technology, and the environment (GRØN DYST). More infor
, Lyngby Campus, Building 221, Ph.
(+45) 4525 2626 ,
, Lyngby Campus, Building 324, Ph.
(+45) 4525 3365 ,
|27 Department of
01 Department of Applied Mathematics and Computer
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Last updated: 04. maj, 2015