Module Number

BIOINF-4510 (bisher: BIO-4510)
Module Title

Applied Statistics for Biomedical Data Analysis
Lecture Type(s)

Seminar
ECTS 3
Work load
- Contact time
- Self study
Workload:
90 h
Class time:
30 h / 2 SWS
Self study:
60 h
Duration 1 Semester
Frequency Irregular
Language of instruction English
Type of Exam

Presentation (about 30 minutes) and written elaboration (approx. 10 pages), leading the discussion once

Content

In this seminar, current topics of applied statistics for bioinformatics data analysis will be discussed. Furthermore, we will also discuss classical concepts of stochastics/statistics and discrete mathematics. These will include, among others, the following: introduction to randomness, elementary and advanced combinatorics, random variables, discrete probability distributions and where they come from, conditional probabilities, Bayes? Theorem, continuous probability distributions, posterior distributions, descriptive statistics, moments of random variables (expectation, variance, ?), parametric models, statistical testing (frequentist view), statistical testing (Bayesian view), parameter estimation: maximum likelihood, parameter estimation in mixture models: EM algorithm, regression (simple linear, logistic, robust, multiple), robust regression, multiple regression, logistic regression. All concepts will be discussed in close relation to to current research in biomedice.

Objectives

The students can independently work with supervision on a challenging topic.
Students gain experience in giving a technical presentation and producing a technical writeup in bioinformatics and in teaching. They can summarize, assess, classify, scientifically correctly represent and present concepts and methods of applied statistics in bioinformatics.
On the one hand, the students will get an overview of modern knowledge in the field of applied statistics in biology and medicine. On the other hand, they will know that there are still many open research questions in this field. By studying current articles and classical concepts, alike, the students have not only improved their reading and learning skills, but also their capability for translational thinking.

Allocation of credits / grading
Type of Class
Status
SWS
Credits
Type of Exam
Exam duration
Evaluation
Calculation
of Module (%)
Prerequisite for participation There are no specific prerequisites.
Lecturer / Other Nahnsen
Literature

Bücher und Forschungsartikel / Books and research articles

Last offered unknown
Planned for Sommersemester 2023
Assigned Study Areas BIO-BIO, BIO-SEM, INFO-INFO, MEDI-APPL, MEDI-INFO, MEDZ-SEM, ML-CS