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BFB12
Biostatistical Foundations in BioinformaticsCourse Timetable (provisional) |
| BFB12 | Biostatistical Foundations in Bioinformatics |
| Mon, Dec 3rd |
Day #1
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| 09:30 - 11:00 |
Descriptive Statistics Describing and summarizing data. Summary statistics and plots for univariate, bivariate and multivariate data. |
| 11:00 - 11:30 | Coffee Break |
| 11:30 - 12:30 | Basic exploratory data analysis with R. |
| 12:30 - 14:00 | Lunch Break |
| 14:00 - 16:00 | Review of probability theory Probability, Random variables and their properties. Distributions. Independence and conditional probability. P-value and E-value. |
| 16:00 - 16:30 | Tea Break |
| 16:30 - 18:00 | Distributions in R: probabilities, densities, simulation. |
| Tue,Dec 4th |
Day #2
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| 09:30 - 11:00 |
Statistical inference I: Sampling distributions. Maximum likelihood estimation. |
| 11:00 - 11:30 | Coffee Break |
| 11:30 - 12:30 |
Statistical inference II: Expectation-Maximization (EM) algorithm. |
| 12:30 - 14:00 | Lunch Break |
| 14:00 - 16:00 |
Statistical inference III: Confidence intervals. Hypothesis testing (parametric tests). |
| 16:00 - 16:30 | Tea Break |
| 16:30 - 18:00 |
Statistical inference IV: Hypothesis testing (non-parametric tests). |
| Wed, Dec 5th |
Day #3
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| 09:30 - 11:00 |
Monte Carlo and Bootstrap methods I Tests and confidence intervals. |
| 11:00 - 11:30 | Coffee Break |
| 11:30 - 12:30 |
Monte Carlo and Bootstrap methods II Permutation tests. |
| 12:30 - 14:00 | Lunch Break |
| 14:00 - 16:00 |
Multiple testing issues I |
| 16:00 - 16:30 | Tea Break |
| 16:30 - 18:00 |
Multiple testing issues II |
| Thu, Dec 6th |
Day #4
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| 09:30 - 11:00 |
Bayesian inference I Bayes' Theorem. Principles of Bayesian Methodolgy. Gibbs sampling. |
| 11:00 - 11:30 | Coffee Break |
| 11:30 - 12:30 |
Bayesian inference II: Applications in population genetics and phylogeny. |
| 12:30 - 14:00 | Lunch Break |
| 14:00 - 16:00 |
Design of experiments I ANOVA: one-way, two-way, repeated measures. |
| 16:00 - 16:30 | Tea Break |
| 16:30 - 18:00 |
Design of experiments I Factorial design. Latin Squares. |
| Fri, DEC 7th |
Day #5
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| 09:30 - 11:00 |
Multivariate statistical methods: Principal component analysis. |
| 11:00 - 11:30 | Coffee Break |
| 11:30 - 12:30 |
Supervised and unsupervised classification I: Cross-validation. Neural netwoks. K-Nearest neighbors. Linear discriminant analysis. |
| 12:30 - 14:00 | Lunch Break |
| 14:00 - 16:00 |
Supervised and unsupervised classification II Support vector machine (SVM). Hierarchical clustering. K-Means. |
| 16:00 - 16:30 | Tea Break |
| 16:30 - 18:00 |
Practical exercises. Final wrap-up session. |
| Course Homepage |
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Instituto Gulbenkian de Ciência, Apartado 14, 2781-901 Oeiras, Portugal Last updated: November 1st 2012 |