Simulation of Distributions and Monte-Carlo Methods

Softwarepraktikum im WS 07/08

Important News

• For the seminar go here
• Preliminary Discussion: will be announced soon!(changed!)

Description

Computational Biology extensively uses statistics and probability theory to accept/reject hypotheses, compute significance values as well as confidence intervals. The central concept is the random variable with its main characteristic: the distribution. Some distributions can be computed analytically, others are only accessible by simulations. Furthermore, visualization of distributions can be nicely used to support understanding of many concepts of probability theory and statistics. Hence, we will discuss applications in computational biology involving distributions, compute/simulate the distributions, and (most importantly) use the visualization to understand standard concepts of statistics and probability theory. In the second part, we will approach distributions which are infeasible to simulate. In this case, we will use Monte-Carlo methods (i.e. importance sampling) for the computation. Again, we will learn standard concepts by looking at the visualized distributions.

This course is for students who are interested in probability theory and statistics. We assume that everybody has successfully finished the course for statistics (Statistik 1 in the 3rd semester). Attendance of the advanced course of statistics (Multivariate Statistik or Statistik 2) is advantageous but not required. The goal of the course is to lose all fear of touching random variables.

Links

Homepage der Abteilung Computational Molecular Biology am Max-Plack-Institut für Molekulare Genetik.

Zum Studiengang Bioinformatik an der FU Berlin.