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1. Acknowledgements
2. Compute and plot Receiver Operating Characteristic (ROC) and Precision-Recall (PR) curve
3. Cookbook
4. Create a discrete alphabet
5. DSHMM
6. Dessert: Alignments, Utils, and goodies
7. Dispom
8. Downloads
9. Dream5
10. FAQs
11. First main course: SequenceScores
12. FlowCap
13. GenDisMix
14. Getting started
15. Hauptseite
16. Implementation of a homogeneous Markov model of order 0 based on AbstractModel
17. Imprint
18. Intermediate course: Optimization
19. Intermediate course: XMLParser, Parameters, and Results
20. Loading data
21. Main Page
22. MeDIP-HMM
23. MiMB
24. MiMB Example
25. MiRNAs
26. MotifAdjuster
27. No Access
28. PHHMM
29. Performing a 10-fold cross validation
30. Prior
31. Projects
32. Quick start: Jstacs in a nutshell
33. Recent changes
34. Recipes
35. Saving and loading a model
36. Second main course: Classifiers
37. Starter: Data handling
38. Test
39. Train classifiers using GenDisMix (a hybrid learning principle)
40. Train classifiers using MCL and MSP
41. Training a classifier and classifying new sequences
42. Using the REnvironment
43. Workshop

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