- Docente: Pier Luigi Martelli
- Crediti formativi: 4
- SSD: BIO/10
- Lingua di insegnamento: Inglese
- Modalità didattica: Convenzionale - Lezioni in presenza
- Campus: Bologna
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Corso:
Laurea Magistrale in
Bioinformatics (cod. 8020)
Valido anche per Laurea Magistrale in Bioinformatics (cod. 8020)
-
dal 15/10/2024 al 25/10/2024
Conoscenze e abilità da conseguire
At the end of the course the student will acquire the basic knowledge of computational methods necessary for analysing biological data in the omic era.
Contenuti
Basics concepts of Linear Algebra
-) Vectors and matrices: basic definitions and operations.
-) Linear transformations in vector spaces.
-) Inverse matrix, Invertibility, Determinants.
-) Eigenvalues and Eigenvectors: applications to Principal Component Analysis.
Basics concepts of Calculus
-) Functions in R. Inverse functions.
-) Derivatives. Maximization and minimization,
-) Integrals.
-) Functions in R2.
-) Partial derivatives. Gradient. Maximization and minimization.
-) Constrained Maximization and Minimization: Lagrange's multipliers.
Basic concept of Probability and Statistics
-) Joint probability, conditional
probability, Bayes' theorem.
-) Discrete probability distributions: Binomial, Poisson
-) Continuous probability distributions: Normal, Boltzmann,
Student, Chi-square, Gumbel (Extreme value)
-) Mean, median, mode, variance.
-) p-value and E-value
-) Tests for statistical significance: Student, Fisher,
Chi-square
Testi/Bibliografia
Slides of the lectures
Reviews and web sites provided during the lectures
Metodi didattici
Lectures and practical sessions
Modalità di verifica e valutazione dell'apprendimento
Written test
Exercises will assess the ability of the students in tackling basic vector and matrix maniulation, basic calculus, statistical and probabilistic problems.
Orario di ricevimento
Consulta il sito web di Pier Luigi Martelli