Recent technological advances in molecular biology and genetics have made it possible to gather very large amounts of data about the structure and regulation of genes. These data can be used to help address important biological questions such as structural and functional prediction, classification of protein molecules, elucidation of the molecular basis for human genetic disease, or reconstruction of evolutionary history. For the effective utilization of such data there is a growing demand for tools provided by mathematics, statistics and computer science.

Many biological structures and processes are intrinsically stochastic. Increasingly, stochastic models are being introduced in analysis and interpretation of biological phenomena and genomics data. A variety of probabilistic and statistical techniques are used for mathematical modeling in biology and medicine. Examples include HMM models for DNA and protein sequence, clustering and tree construction in phylogenetic inference, likelihood or Bayesian statistical inference in pedigree analysis and association studies, genetic linkage analysis, microarray analysis, spatial patterns and processes. The ultimate challenge for bioinformatics and an important part of the final goal of biomedical science in general is the complete molecular understanding of a living organism. Mathematics and computer science can provide the tools to achieve this.

Programme

The Master Class on Stochastics in Molecular Biology and Genetics is organized within the regular (two-year-long) Master programme Stochastics and Financial Mathematics (SFM) which is run jointly by three universities: University of Amsterdam, University of Utrecht and Vrije Universiteit Amsterdam. Approximately half courses will take place at the University of Utrecht. The other half of the courses will take place at the Vrije Universiteit Amsterdam, which can be reached from Utrecht by a 31 minutes train journey.

1st Semester

1. Introduction to molecular biology (lecturer from the biology faculty (UU))
2. Mathematical statistics (E. Belitser (UU))
3. Probability models for DNA evolution (R. Meester (VU))
4. Seminar computational biology (A. Siebes (UU))

2nd Semester

1. Statistical genetics (A. van der Vaart (VU))
2. Survival analysis and missing data (R. Gill (UU))
3. High dimensional data and multivariate analysis (A. van der Vaart, S. van de Geer (UL), C. Klaassen (UvA))
4. Seminar statistics and probability in molecular biology and genetics (M. de Gunst (VU))

Here: UU - Utrecht University, VU - Vrije Universiteit Amsterdam, UvA - University of Amsterdam, UL - Leiden University. Possibly other lecturers may become involved with the programme in due course.
In the seminars the students themselves are the main speakers. There is a weekly consultation hour for individual questions.

How to apply

Applicants should have completed at least three years of undergraduate studies in mathematics (or a related field with a strong mathematical background). In particular, a basic knowledge of probability theory and mathematical statistics is required for successful participation. To apply for the Master Class or Spring School send the following documents to the secretariat of the MRI:

• curriculum vitae (including the following details: first name, surname, date of birth, nationality, address, postal code, city, country, phone number, fax, email address)
• academic record: list of subjects/classes taken at university, subjects for degree examination, photocopy of diploma (if available)
• recommendations from members of the academic staff of the home university (at least one)
• a summary of financial circumstances (if financial support is necessary).

The application deadline for the 2004/2005 Master Class is April 15, 2004, for non-EU residents and July 1, 2004 for EU-residents, by which date applications and the necessary documents must have been received by the MRI.

About the Master SFM