Statistics, Probability and Applications in Bioinformatics Prof. Dr. Sven Rahmann (4V+2Ü; specialized lecture: From elementary probability to complex statistical models)

Registration for this course is open until Sunday, 31.10.2021 23:59.

News

21.10.2021

FIrst Assignment Published

Dear all,

please find the first assignment sheet under "Materials". Have fun with the tasks. For the programming task, we recommend Python. If you use a different language, please remember that you need arbitrary precision integers; there are some huge numbers... Read more

Dear all,

please find the first assignment sheet under "Materials". Have fun with the tasks. For the programming task, we recommend Python. If you use a different language, please remember that you need arbitrary precision integers; there are some huge numbers involved!

19.10.2021

Lecture starts today (Tue Oct 19!)

Dear all, the lecture starts today (Tue Oct 19) at 08:30. If you miss it, don't worry! A recording is available; the link in the Materials section. You need to be registered, though, to access it. There will be no tutorials this week, but you will receive a first... Read more

Dear all, the lecture starts today (Tue Oct 19) at 08:30. If you miss it, don't worry! A recording is available; the link in the Materials section. You need to be registered, though, to access it. There will be no tutorials this week, but you will receive a first problem set on Thursday.

05.10.2021

Registration now open

You can now register for this course. When selecting a tutorial, please note that the on-campus tutorial is subject to regulations imposed by the university (3G). If in doubt, consider the online tutorial. Depending on the number of registrations, we may offer more... Read more

You can now register for this course. When selecting a tutorial, please note that the on-campus tutorial is subject to regulations imposed by the university (3G). If in doubt, consider the online tutorial. Depending on the number of registrations, we may offer more than one online tutorial.

 

Statistics, Probability and Applications in Bioinformatics

Specialized course, B.Sc. and M.Sc. Bioinformatics, Saarland University.
Elective course, M.Sc. CS, DS/AI, and related, Saarland University

Prerequisites Mathematics (especially analysis and linear algebra); solid programming skills (required!)
Credits 9 ECTS credits
Required time 4V+2Ü (4 hours of lectures, 2 hours of tutorials per week)
Language English
Registration click on Registration in the menu header
Details available after registration in the Course Management system
Times Tuesday + Thursday, 08:30 - 10:00 (starts on Tue Oct 19!)
Mode online lecture; both online and offline tutorial options
Link Zoom link available under "Materials" after registration
   

Target audience (IMPORTANT!)

This course is offered as a specialized lecture in the B.Sc. or M.Sc. Bioinformatics degrees, for 9 ECTS credits.
It can be taken by other students at Saarland Informatics campus (CS, DS/AI, etc.), but please discuss this with the instructor.
There is some overlap with StatsLab, so if absolutely required, you can do this course as a substitute for StatsLab (with a reduced exam), but note that this course is designed for a different audience.

You will need 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 where they come from
  • probability distributions and OOP, scipy.stats
  • conditional probabilities
  • Bayes’ Theorem, simple version
  • continuous probability distributions
  • a glimpse at measure theory
  • posterior distributions

Statistics

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

Stochastic Processes

  • stochastic processes
  • Poisson process
  • models for random sequences
  • Markov chains
  • Markov processes: models of sequence evolution
  • Hidden Markov Models and applications
  • Probabilistic Arthimetic Automata and applications
  • distribution of DNA Motif Occurrences: compound Poisson
  • significance of pairwise sequence alignment
  • the PCR process

Applications in Bioinformatics

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


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