LMU, Department of Statistics, Summer
Statistics and Computational Biology
||Friday 28 April 2006,
||Session A: 9 June 2006
Session B: 23 June 2006
Session C: 7 July 2006
Session D: 14 July 2006
(Friday afternoon, 2-6pm).
||Seminar room, Dept. of Statistics, Ludwigstr.
||Send email to Korbinian
In this seminar we discuss challenges and problems in
the statistical modeling and inference of complex
high-dimensional dynamical systems. The main topics
- High-dimensional models for complex dynamic systems
(time series models, graphical models, stochastic
differential equations etc.),
- statistical approaches for their efficient
(regularized) inference and model selection, and
- application to biological data (mostly related to
See the PDF flyer and the
detailed reading list for
Prerequisites and Requirements:
Knowledge of multivariate analysis, time series and some
bits of Bayesian inference and penalized likelihood
inference is advantageous.
In order to obtain a certificate ("Schein") you need
- present a talk (45 mins) on the chosen topic
- give a short talk (10 mins) on somebody else's topic
- hand in a written expose ("Ausarbeitung") about your
topic (10-15 pages),
- write all slides in English (preferentially using the
- attend at all sessions, and
- actively participate in the discussion following each
Schedule and Program:
Click on the name of the main speaker for download of the slides!
Session A: Regularized inference (9 June
Session B: Multiple testing and model selection (23
||Local fdr theory
||Papers 5 and 6
||Large-scale differential expression
||FDR and model selection
Session C: Dynamic models (7 July 2006):
||Inference of high-dimensional VAR model
||State-space models inferred by variational
||Random walk and diffusion models
||Paper 11 including supplements 1, 2, 3, and 4
Session D: Graphical models (14 July 2006):
||Graphical models for time series data
||Constructing large-scale graphical models
||Spirtes PC algorithm
- Efron, B., and C. Morris. 1975. Data analysis using
Stein's estimator and its generalizations. JASA
- Friedman, J.H. 1989. Regularized discriminant
analysis. JASA 84:165-175.
- Tibshirani, R, et al. 2002. Diagnosis of multiple
cancer types by shrunken centroids of gene
expression. PNAS 99:6567-6572.
- Hastie, T, and R. Tibshirani. 2004. Efficient quadratic
regularization for expression arrays. Biostatistics
- Efron, B. 2004. Large-scale simultaneous
hypothesis testing: the choice of a null-hypothesis.
- Efron, B. 2005. Local false discovery rates.
- Lönnstedt, I., and T. Britton. 2005. Hierarchical Bayes
models for cDNA microarray gene expression.
- Gosh, D., W. Chen, and T. Raguhathan. 2004. The false discovery rate: a
variable selection procedure. Preprint.
- Ni, S. and D. Sun. 2005. Bayesian
estimates for vector autoregressive models. J.
Business. Economic Statistics. 23:105-117
- Beal, M.J., F. Falciani, Z. Gharamani, C. Rangel, and
D. Wild. 2005. A
Bayesian approach to reconstructing genetic regulatory
networks with hidden factors. Bioinformatics
- Brockmann, D., L. Hufnagel, and T. Geisel. 2006.
laws of human travel. Nature 439:462-465.
- Bach, F. R., and M. I. Jordan. 2004. Learning graphical models
for stationary time series. IEEE Transactions on
Signal Processing 52:2189-2199.
- Jones, B., C. Carvalho, A. Dobra, C. Hans, C. Carter,
and M. West. 2005. Experiments in stochastic
computation for high-dimensional graphical models.
Statistical Science 20:388-400
- Kalisch, M, and P. Bühlmann. 2006. Estimating
high-dimensional directed acyclic graphs with the
Further links regarding systems biology:
July 10, 2006