News

Extra Exercises

Written on 25.10.25 by Inês Ferreira

The extra exercises from last week have been posted on CMS.
A forum post is also available with answers to the questions raised during Thursday’s tutorial.

Assignment 02 online

Written on 25.10.25 by Sven Rahmann

Assingment 02 is online with a few different exercises concerning combinatorics, approximations and discrete distributions, notably Poisson. 

Today's Tutorial Cancelation

Written on 22.10.25 by Inês Ferreira

Good morning everyone,

Starting tomorrow, the tutorials will be held in room 0.01 (same room as the lectures).

Unfortunately, since no room is available today, the tutorial is canceled.

See you tomorrow,

Inês

Tutorial Schedule Update

Written on 20.10.25 by Inês Ferreira

Dear all,

Thank you for completing the poll regarding tutorial times. We have decided to offer two tutorial sessions each week:

Wednesday, 14:00–16:00
Thursday, 08:00–10:00

See you soon,
Inês

Materials and First Assignment

Written on 17.10.25 by Sven Rahmann

There are now lecture slides for this and next week among the materials, as well as the first assignment, which starts today and should be submitted by next Friday (24.10.). Have a nice weekend!

Tutorial - Poll

Written on 16.10.25 by Inês Ferreira

Hi everyone,

There is now a poll to find the best weekly tutorial slots. You can find the link under Materials. Please fill it out as soon so that we can set the tutorial date before next week.

Thank you.

Show all

BioStatsLab (a BSc Bioinformatics Replacement for MInf3)

Basic mandatory course, B.Sc. Bioinformatics, Saarland University.
This course is not available for credit points to students of other programs! You are welcome to audit, but will not get ECTS.

Prerequisites Mathematics (MInf1+Minf2, especially some  analysis and linear algebra); solid programming skills
Credits 9 ECTS credits
Required time 4V+2Ü (4 hours of lectures, 2 hours of tutorials per week)
Language English (although this is a basic course, it also serves as an additional prerequisite for international Master students,
and is hence given in English!)
Registration click on Registration in the menu header
Materials Materials will be available after registration under Information > Materials
Times
 
 
Lecture: Wednesday 08:30 - 10:00 and Friday 12:15 - 13:45.
Tutorials: Wednesday, 14:00–16:00, Thursday, 08:00–10:00
Office Hour: TBA
Mode lecture in presence in E2.1, room 001
Link https://cms.sic.saarland/biostatslab25
Instructor Prof. Dr. Sven Rahmann
Tutorials M. Sc. Inês Alves Ferreira
Exam Written exam (up to 3h) at the end of the semester.
Requirements to participate in the exam:
- No score requirements for the exercises (pointless since LLMs can solve all of these)
- Presentation of your solved exercises before the tutorial group (as explained in the first lecture)

 

Target audience 

This course is offered as a basic lecture in the B.Sc. Bioinformatics program as a replacement for Mathematics for Informaticians 3 (MInf3).
Thus it should be taken in the 3rd semester, after completing MInf1 and MInf2, as well as Programming 1 & 2.
It should be taken in parallel to Bioinformatics 1 during the B.Sc. Bioinformatics program.

You will need some programming skills to qualify for the exam. Best would be Python, but you can use a language of your choice.
Please do not waste your time by attempting this course without a solid basis in programming.

 

Topics

The following topics will be covered in the course; additional topics may be included, depending on time and current events.

Probability

  • randomness
  • uniform distributions on finite sets (Laplace spaces)
  • elementary and advanced combinatorics
  • finite, discrete and continuous probability spaces
  • random variables
  • discrete probability distributions and how they are derived
  • probability distributions and OOP, scipy.stats
  • conditional probabilities
  • Bayes’ Theorem, simple version
  • moments of random variables (expectation, variance, …)
  • continuous probability distributions
  • a glimpse at measure theory
  • posterior distributions

Statistics

  • descriptive statistics
  • parametric models
  • statistical testing (frequentist view)
  • statistical testing (Bayesian view)
  • parameter estimation: moments, maximum likelihood
  • parameter estimation in mixture models: EM algorithm
  • regularization and Bayesian view on estimation
  • linear regression
  • robust regression
  • multiple regression
  • logistic regression

Stochastic Processes

  • stochastic processes
  • models for random sequences
  • Markov chains
  • Markov processes: models of sequence evolution
  • Hidden Markov Models and applications
  • Probabilistic Arthimetic Automata (PAAs) and applications
  • the Poisson process
  • distribution of DNA motif occurrences: compound Poisson
  • significance of pairwise sequence alignment

Applications in Bioinformatics

  • tests for differential gene expression
  • Bayesian view on differential gene expression
  • high-dimensionality low-sample problem
  • multiple testing

Multi-dimensional analysis (compact, 1 week)

  • partial / total differentiability
  • high-dimensional optimization

 

 

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