Molecular Cell Biology
De combinatie van de vakken Moleculaire Celbiologie, Life Sciences en Biochemie geven een complete introductie van de werking van de levensprocessen in de cel. Studenten maken kennis met de moleculaire wereld en leren een moleculaire manier van denken aan. In de Moleculaire Celbiologie nemen we het functioneren van de kleinste levende eenheid, de cel, als
Machine Learning (TU Delft)
The goal of the course is to acquaint students with the basic Machine Learning concepts and algorithms. Specifically, the course will cover parametric and non-parametric density estimation, linear and non-linear classification, unsupervised learning including clustering and dimensionality reduction, performance evaluation of predictive algorithms and ethical issues in machine learning.
Life Sciences
De combinatie van de drie vakken in Q1 van BSc LST: Moleculaire Celbiologie, Life Sciences en Biochemie, geeft een complete introductie van de werking van de levensprocessen in de cel. Het klonen van DNA voor eiwit expressie en vervolgens zuiveren van een enzym, receptor, biomarker of ander eiwit zijn vaak de eerste stappen die nodig
Modelling and Problem Solving
The course covers major (combinatorial) solving approaches, namely constraint programming, integer programming, boolean satisfiability, dynamic programming and decision diagrams, and local search. The course focuses on modelling practical problems, expressing them in the surveyed paradigms; algorithms for solving such problems are covered in the follow-up “Constraint Solving” course. The topic of genetic algorithms is reserved
Machine Learning in Bioinformatics
Learning from patterns in molecular biology data plays an important role in diagnosing disease, discovering new targets for therapy, and more generally in answering biological questions that lead to an improved understanding of biological systems with relevance to human health, industry, biotechnology, and agriculture. This course focuses on methodology for the analysis of high-dimensional data