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Bioinformatics Algorithms - ED 24/Série 3

Faculté de gestion: Ecole doctorale (FBM-DOCT)

Responsable(s): Christophe Dessimoz, David Gfeller

Période de validité: 2016 ->

Horaires du cours (Apériodique)

Date Lieu Remarque Thématique Intervenant(s)
27.02.2024 de 09:15 à 12:00 Salle 336, Amphipôle, Quartier UNIL-Sorge Introduction. How computers work; fundamentals of algorithm and complexity theory. Christophe Dessimoz
05.03.2024 de 09:15 à 12:00 Salle 336, Amphipôle, Quartier UNIL-Sorge Exact sequence matching I: read mapping, indexing Christophe Dessimoz
12.03.2024 de 09:15 à 12:00 Salle 336, Amphipôle, Quartier UNIL-Sorge Exact sequence matching II: hashing, edit distances. Christophe Dessimoz
19.03.2024 de 09:15 à 12:00 Salle 336, Amphipôle, Quartier UNIL-Sorge Approximate sequence matching: dynamic programming Christophe Dessimoz
26.03.2024 de 09:15 à 12:00 Salle 336, Amphipôle, Quartier UNIL-Sorge Alignment significance: permutation test, parameter estimation Christophe Dessimoz
09.04.2024 de 09:15 à 12:00 Salle 336, Amphipôle, Quartier UNIL-Sorge Networks I: Introduction to different types of networks. Graph representation and data structure. Graph and tree traversals. David Gfeller
16.04.2024 de 09:15 à 12:00 Salle 336, Amphipôle, Quartier UNIL-Sorge Networks II: Clustering. David Gfeller
23.04.2024 de 09:15 à 12:00 Salle 336, Amphipôle, Quartier UNIL-Sorge Networks III: Neural networks. David Gfeller
30.04.2024 de 09:15 à 12:00 Salle 336, Amphipôle, Quartier UNIL-Sorge Networks IV: Convolutional neural networks. David Gfeller
07.05.2024 de 09:15 à 12:00 Salle 336, Amphipôle, Quartier UNIL-Sorge Cross-validation, avoiding overfitting David Gfeller
14.05.2024 de 09:15 à 12:00 Salle 336, Amphipôle, Quartier UNIL-Sorge Hidden Markov models. Forward-backward algorithm. Christophe Dessimoz
21.05.2024 de 09:15 à 12:00 Salle 336, Amphipôle, Quartier UNIL-Sorge Minimizers and MinHashing Christophe Dessimoz
28.05.2024 de 09:15 à 12:00 Salle 336, Amphipôle, Quartier UNIL-Sorge Conclusion. Review key ideas, next steps, feedback Christophe Dessimoz

Cours (optionnel)

Annuel
Apériodique
Langue(s) d'enseignement: anglais
Public: Oui
Crédits: 3

Objectif

 

The course aims at improving the student’s programming skills by gaining a deep understanding of some of the key algorithms in bioinformatics, with a special emphasis on sequence and graph algorithms.

 

 

 

Contenu

 

Students will learn widely applicable concepts, such as asymptotic time complexity, binary search, suffix trees, dynamic programming, hashing, hidden Markov models, and neuronal networks.

 

Practicals and home assignments are essential parts of the course. The language of the course is Python, though the concepts covered in the course are applicable to all computer languages.

Evaluation

Mandatory assessment: 20 min oral examination
Final test:
date to be confirmed

Bibliographie

-

Exigences du cursus d'études

The course assumes familiarity with basic programming concepts (variable and function declaration, arrays, for-loops, conditional statements, etc.). Algorithms are introduced from a practical angle so the mathematical formalism is kept at a minimum.

Conditions d'octroi

Participation active attestée par le responsable. Final test that will take place in summer exam

Conditions d'accès

Inscription auprès de l'Ecole doctorale. Série 3

Informations supplémentaires

http://lab.dessimoz.org/teaching/bioinfalgo/

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